How to find Elixir developers in 2026: A sourcing guide

Elixir is built on the BEAM virtual machine, the same runtime that has powered Ericsson's telecom infrastructure since the late 1980s. Discord handles 56 million monthly active users on Elixir. Pinterest replaced 200 Python servers with 4 Elixir servers and saved $2 million per year. Bleacher Report serves 3 million daily users on Phoenix. These companies chose Elixir because their concurrency and uptime requirements broke other options.

Like Go and Rust, Elixir's ecosystem is overwhelmingly open source and lives on GitHub. Phoenix, LiveView, Ecto, Oban, Broadway, Nerves — the tools that production Elixir systems depend on are all developed in the open. That makes GitHub the single best sourcing channel for Elixir talent. We covered Elixir briefly in our niche language sourcing guide — this is the deep dive.

This guide covers where Elixir developers work on GitHub, what quality signals separate experienced BEAM engineers from developers who completed a tutorial, why OTP patterns matter more than syntax knowledge, and how to build a sourcing workflow that finds Elixir engineers before they start looking.

The Elixir developer market in 2026

Elixir has one of the smallest developer pools of any language with meaningful production adoption. Estimates place the global community at roughly 100,000 active practitioners. For comparison, Go has 3 to 4 million, Python has 16 million-plus, and JavaScript has over 20 million. The Stack Overflow Developer Survey puts Elixir usage at approximately 1 in 50 developers. That ratio is what makes Elixir hiring so difficult: the people who write Elixir in production are almost all employed, almost all senior, and almost all ignoring recruiter outreach that does not demonstrate any understanding of what they do.

But there is a counterbalancing signal. Elixir is the second-most desired language to learn (behind Rust) in the same Stack Overflow survey. The community is growing. New developers are entering the ecosystem. The problem is that experienced production engineers — the ones who understand OTP supervision trees, distributed systems on the BEAM, and Phoenix at scale — remain scarce and will for the foreseeable future.

Compensation reflects the scarcity. Elixir is the fifth highest-paid programming language globally. In the US, junior to mid-level Elixir developers average around $117,000. Senior developers average $152,000, with remote senior roles reaching approximately $163,000. The top end can go higher at companies like Discord and in fintech, where Elixir's concurrency model is a genuine competitive advantage. These salaries reflect a real supply-demand imbalance. The pool is small and the companies that need Elixir engineers are not flexible on the requirement — no other language gives them the same concurrency model on the same runtime.

Hiring cycles for Elixir developers run 45 to 90 days, and roles requiring deep OTP expertise or distributed systems experience can take longer. The bottleneck is not interview pipeline efficiency. It is finding qualified candidates in the first place. The functional programming paradigm, the actor model, and OTP design philosophy require deliberate study and real project exposure. You cannot learn OTP on a weekend, and you cannot casually transition from Python or JavaScript without investing meaningful time.

Where do Elixir engineers actually concentrate? Real-time systems: chat platforms, notification services, live dashboards, collaborative editing. Fintech and payments: transaction processing, fraud detection, anything requiring high throughput with strict reliability guarantees. IoT and embedded systems via the Nerves framework. Web applications with real-time requirements via Phoenix LiveView. Data pipelines and stream processing via Broadway. The thread connecting all of these is systems that must stay up, handle massive concurrency, and fail gracefully.

Discord, Pinterest, the Financial Times, Toyota Connected, Square Enix, Plausible Analytics, PagerDuty, Bleacher Report — these are not early-stage startups experimenting. They chose Elixir because their concurrency and reliability requirements outgrew what mainstream languages could handle. That track record matters when you are recruiting. Candidates want to know their language choice has a real production future, and this list answers the question.

Where Elixir developers contribute on GitHub

Elixir's open source ecosystem is where the strongest engineers are most visible. Because the community is small, individual contributions are more traceable than in larger ecosystems. GitHub is one of the most effective sourcing channels for Elixir engineers precisely because almost every production tool in the ecosystem is developed in the open.

The language itself. elixir-lang/elixir is the core repository — the compiler, standard library, and toolchain. Contributors here work on the language's foundations. This is a small, selective group maintained primarily by José Valim and a handful of core contributors. Even issue discussion and triage on this repo indicates a developer who understands Elixir at a foundational level.

Web frameworks. phoenixframework/phoenix is the center of gravity for the Elixir web ecosystem. It is to Elixir what Rails is to Ruby, but with built-in support for real-time features via Channels and Presence. phoenixframework/phoenix_live_view is changing how teams build interactive UIs — server-rendered HTML with real-time updates over WebSocket, eliminating the need for a separate JavaScript SPA in many cases. Contributors to either of these repos understand both Elixir and modern web architecture well enough to be building the tools other teams depend on.

Data and database. elixir-ecto/ecto is the database wrapper and query DSL used by virtually every Elixir application. It handles schemas, migrations, validations, and composable queries. elixir-ecto/postgrex is the PostgreSQL driver. Contributors here understand data layer design, query composition, and the nuances of building database abstractions in a functional language.

GraphQL. absinthe-graphql/absinthe is the GraphQL toolkit for Elixir. The Financial Times runs their subscription and user management GraphQL API on Absinthe. Contributors to this project understand API design, schema-first development, and the intersection of GraphQL with Elixir's concurrency model — Absinthe can resolve fields in parallel using BEAM processes.

Background processing and data pipelines. sorentwo/oban is the de facto standard for background job processing in Elixir, backed by PostgreSQL. dashbitco/broadway handles data ingestion and processing pipelines with built-in backpressure, batching, and fault tolerance. These are the projects behind production workloads at scale. Contributors understand job scheduling, queue management, and stream processing.

IoT and embedded systems. nerves-project/nerves brings Elixir to embedded devices and IoT. It produces firmware images that boot directly into the BEAM VM, giving embedded systems the same fault-tolerance guarantees that Elixir provides on servers. Contributors here bridge software and hardware, understanding cross-compilation, firmware updates, and the constraints of resource-limited environments. This is a niche within a niche, but Nerves engineers tend to be strong generalists who can work across the full stack.

Numerical computing and machine learning. elixir-nx/nx is Elixir's numerical computing library, providing tensor operations and compiler backends for CPU and GPU. elixir-nx/livebook is an interactive notebook environment (similar to Jupyter) for Elixir. These projects are led by José Valim and are the newest major addition to the Elixir ecosystem. Contributors here tend to have both Elixir depth and numerical computing backgrounds.

Tooling and packages. elixir-lang/ex_doc is the documentation generator used across the ecosystem. Beyond specific repositories, hex.pm (Elixir's package registry) hosts thousands of packages with publicly listed authors. If someone maintains a well-documented, widely-used hex.pm package, they are almost certainly a senior Elixir developer.

Quality signals in Elixir code

If you are evaluating Elixir code with an object-oriented eye, you will misjudge it. Elixir is a functional language with a concurrency model that has nothing in common with Python, JavaScript, or Java. Seniority signals on GitHub apply broadly, but Elixir has specific markers of expertise that are unique to the BEAM ecosystem.

OTP design patterns. OTP (Open Telecom Platform) is what makes Elixir special. An experienced Elixir developer designs systems around GenServers, Supervisor trees, and Application structure. The key signal is not whether someone uses a GenServer — it is whether they use one appropriately. A developer who wraps everything in a GenServer when a simple module function would suffice is showing beginner habits. Conversely, well-structured supervision trees with restart strategies (:one_for_one, :rest_for_one, :one_for_all) matched to failure domains signal deep understanding of how the BEAM manages fault tolerance.

Pattern matching and guard clauses. Elixir uses pattern matching pervasively — in function heads, case statements, and with expressions. An experienced developer writes multiple function clauses with pattern-matched arguments rather than large if/cond blocks. Guard clauses (when is_binary(x), when length(list) > 0) add precision to function dispatch. This is the most visible indicator of whether someone thinks in Elixir or is translating from another language. A developer who writes a 50-line function with nested conditionals instead of four clean function clauses with pattern matching is bringing habits from Python or JavaScript.

Pipeline operator and functional composition. The |> operator is idiomatic Elixir. Experienced developers build data transformation pipelines that read top-to-bottom, making the flow of data through a series of transformations immediately clear. But overuse is a signal too — deeply nested pipelines, piping into anonymous functions, or forcing a pipeline where a simple variable assignment would be clearer all indicate style-over-substance. The best Elixir code uses pipelines where they clarify intent and breaks them where they do not.

Fault tolerance design. Elixir inherits Erlang's "let it crash" philosophy. Processes are designed to fail and restart rather than defensively catching every possible error. If you are used to try/catch, this will seem reckless. It is the opposite. A developer who writes defensive error handling everywhere in Elixir is bringing habits from another ecosystem. A developer who designs for failure recovery through supervision — isolating failure domains, choosing appropriate restart strategies, and letting supervisors handle recovery — actually understands the BEAM. This is the difference between an Elixir developer and a developer who writes Elixir syntax.

Behaviours and protocols. Behaviours (GenServer, Supervisor, Application, and custom behaviours) define contracts that modules implement. Protocols provide polymorphism — the ability to extend functionality for new data types without modifying existing code. An experienced Elixir developer uses these to build extensible, well-structured systems rather than relying on runtime type checks or large case statements. Custom behaviours in particular are a strong signal: they show the developer understands how to design abstractions in Elixir's functional paradigm.

Testing with ExUnit. ExUnit is Elixir's built-in test framework. Strong Elixir developers write comprehensive tests with clear setups, use describe blocks for organization, and test concurrent code (GenServers, processes) correctly — which is non-trivial and a strong quality signal. Property-based testing with StreamData for edge case coverage is an additional positive signal, though less common. Testing async processes, message passing between GenServers, and supervision tree behavior correctly demonstrates a developer who understands the runtime, not just the language.

Hex.pm package publishing. Maintaining a published package on hex.pm shows ecosystem investment beyond application development. Check for clean documentation generated with ExDoc, semantic versioning, a well-designed API that follows Elixir conventions, and download counts. A developer whose package is depended on by hundreds of other projects is almost certainly a senior practitioner. Cross-referencing popular hex.pm packages with their GitHub maintainers is a manual but effective sourcing method.

Elixir and the BEAM ecosystem

The BEAM virtual machine deserves its own section because it is the reason Elixir exists and the reason companies choose it over everything else. The BEAM was created at Ericsson in the late 1980s to power telecom switches. Ericsson's AXD301 ATM switch, running on the BEAM, famously achieved nine nines of availability — 99.9999999% uptime. That is roughly 31 milliseconds of downtime per year. The BEAM was designed from the ground up for systems that cannot go down, and Elixir inherits all of that.

OTP is what separates Elixir from other functional languages. It is not a library you install — it is built into the platform. GenServer gives you a standard way to build stateful server processes. Supervisors watch child processes and restart them when they fail. Applications group related processes into self-contained units with defined lifecycles. Task and Agent handle simpler concurrency patterns. These patterns have been running production telecom infrastructure for decades — they predate most of the languages your candidates learned first.

The "let it crash" model is the hardest concept for developers from other ecosystems to internalize, and it is the most important. Instead of trying to anticipate and handle every possible failure with defensive programming, you design process trees where failures are isolated and automatically recovered. A crashed process does not bring down the system — its supervisor restarts it, and the rest of the application continues running. This is why Elixir systems can hit availability numbers that would take enormous effort in languages without this model. When you are evaluating a candidate, supervision tree design tells you more about their ability than almost any other signal.

LiveView is reshaping how teams think about frontend development. Instead of building separate API and SPA layers — a Hono backend and a React frontend, for instance — LiveView renders HTML on the server and pushes real-time updates to the browser over WebSocket. Teams using LiveView can ship interactive, real-time UIs with significantly less JavaScript. The tradeoff is higher server-side state, but the BEAM's lightweight process model handles this naturally. Contributors to LiveView understand both server-side Elixir and modern UX patterns, which makes them useful for a wider range of roles than most backend specialists.

The Elixir community is small but unusually tight-knit, which matters for sourcing. ElixirConf is the annual conference. ElixirForum is the primary discussion board. The Thinking Elixir podcast and Elixir Slack channel are active community hubs. Because the community is small, one referral from a community member often leads to several strong candidates. Conference speaker lists, forum participants, and podcast guests are underused sourcing channels — they are publicly available lists of engaged Elixir practitioners.

One more thing worth knowing about: cross-pollination with Erlang. Some of the strongest Elixir developers also contribute to Erlang/OTP repositories. These developers understand the VM at the deepest level — they can read the Erlang source code that their Elixir code compiles down to, debug VM-level issues, and leverage Erlang libraries directly. If you see contributions to both elixir-lang/elixir and erlang/otp on the same GitHub profile, that person is worth reaching out to immediately.

How to search for Elixir developers on GitHub

GitHub's search capabilities provide a starting point, but Elixir's small community requires different calibration than searching for JavaScript or Python developers. The niche language sourcing strategies we covered previously apply to Elixir, with adjustments for its specific ecosystem.

Language filter. GitHub allows you to search for users by the language of their repositories. Filtering by language:elixir in repository or code search surfaces developers who actively write Elixir. Because the community is small (roughly 100,000 practitioners), this filter is more targeted than for mainstream languages — nearly everyone who shows up is a real practitioner, not someone who copied a tutorial project. The signal-to-noise ratio is unusually high.

Hex.pm package authors. Hex.pm is Elixir's package registry, and it lists package authors with their GitHub profiles. Packages with high download counts and many dependents indicate senior practitioners who build infrastructure the rest of the ecosystem relies on. Cross-referencing hex.pm download counts with GitHub profiles is one of the most effective manual sourcing methods for Elixir specifically.

Community sources. ElixirForum (elixirforum.com) is the primary discussion board, and active posters are identifiable. ElixirConf speaker lists are publicly available for every year of the conference. Thinking Elixir podcast guests are another traceable source. These are small, well-defined communities where the most active members are not anonymous — they have GitHub profiles, hex.pm packages, and public contribution histories.

Contribution recency. Because the pool is small, even developers with moderate recent activity are worth considering. The threshold for "active" is different for a 100,000-person community than for JavaScript's 20 million-plus. An Elixir developer who has committed meaningful code in the last six months is an active member of a small community, not a casual contributor. Adjust your recency filters accordingly — cast a wider net on timeframe than you would for mainstream languages.

Adjacent language signals. Many Elixir developers come from other backgrounds and write Elixir as a secondary or growing language. The Stack Overflow survey showed 64.5% of Elixir developers came from TypeScript and JavaScript backgrounds. Ruby and Rails developers are another common pipeline into Elixir, given the shared emphasis on developer happiness and productivity. Erlang veterans, Haskell users, and Clojure developers bring functional programming fundamentals that transfer directly. Search for developers whose primary language is Ruby, Erlang, or Haskell but who have Elixir repositories — they may be further along the transition than their profile suggests.

A practical Elixir sourcing workflow

Here is what works, from initial discovery to first outreach.

Step 1: Define the technical profile. "Elixir developer" is too broad to be useful. Are you hiring for real-time systems (Phoenix Channels, LiveView, WebSocket infrastructure)? Data pipelines and stream processing (Broadway, Oban)? IoT and embedded systems (Nerves)? Fintech and payment processing? Each maps to different GitHub repositories, different hex.pm packages, and different contributor communities. An engineer who contributes to Phoenix LiveView has a different skill set than one who contributes to Nerves, even though both write Elixir.

Step 2: Identify target repositories. Based on the technical profile, list the GitHub repositories and hex.pm packages where your ideal candidate would contribute. For real-time web: Phoenix, LiveView, Phoenix Channels. For data processing: Broadway, Oban, Flow. For GraphQL APIs: Absinthe. For IoT: Nerves and its ecosystem. For general infrastructure: Ecto, the core language, and Erlang/OTP repos for deep systems candidates. Map the role to the repos.

Step 3: Extract contributors. Use GitHub's contributor graphs or tools like riem.ai that index GitHub event data at scale. Focus on recent contributors (last 3 to 6 months) with meaningful contributions: code changes, reviews, and design discussions, not typo fixes. Because the Elixir community is smaller than Go or Python, your initial list may be 20 to 50 people rather than 50 to 100. That is expected and fine — the quality-to-volume ratio in a 100,000-person community is much higher.

Step 4: Evaluate profiles. Review each candidate's GitHub profile for the quality signals described above: OTP patterns, pattern matching, supervision tree design, pipeline operator usage. Seniority signals like code review participation and cross-project contributions are even more valuable in a small community where individual reputations are well-known. Check whether they review other people's code, not just write their own.

Step 5: Expand to adjacent backgrounds. Do not limit sourcing to pure Elixir developers. Ruby and Rails developers with Elixir side projects are strong candidates — the migration path is well-established and many successful Elixir teams were built from Rails backgrounds. Erlang veterans bring the deepest VM knowledge. Functional programming enthusiasts with Haskell, Clojure, or F# experience have the right mental model. Check GitHub for Elixir repos from developers whose primary language is something else. Do not require "3 or more years of Elixir experience" — in a community of 100,000, that requirement eliminates most of your viable candidates. Functional programming background and a demonstrated ability to learn matter more than years of Elixir-specific experience.

Step 6: Craft personalized outreach. Generic "I found your profile on GitHub" messages get ignored. Effective developer outreach references specific contributions: "I noticed your Oban plugin for rate-limited job scheduling — we're building a payment processing pipeline on Broadway and your approach to backpressure is exactly what we need." Elixir developers receive fewer recruiter messages than React or Python developers, so well-crafted outreach lands better. But the bar for technical specificity is higher because the community is smaller and more technical — generic messages are spotted instantly.

Step 7: Scale with tooling. The manual workflow above is effective but the small community means you will exhaust your target repos quickly. Tools like riem.ai automate the discovery and evaluation steps by analyzing 30 million-plus GitHub events per month and surfacing Elixir developers based on actual contribution patterns. Instead of manually cross-referencing hex.pm packages and reviewing profiles one by one, you can describe the technical profile in natural language ("Elixir developers who contribute to real-time web frameworks and have experience with Phoenix Channels or LiveView") and get a ranked list of candidates with contribution summaries and quality scores.

Frequently asked questions

How many Elixir developers are there?

Roughly 100,000 active Elixir practitioners globally as of 2026, based on Stack Overflow and community estimates. That makes it one of the smallest pools of any language with meaningful production adoption — roughly 1 in 50 developers according to the Stack Overflow Developer Survey. The small pool is offset by high average quality: developers who choose Elixir tend to be experienced engineers who deliberately selected a functional, fault-tolerant platform. The community is growing (Elixir is the second-most desired language to learn, behind Rust), but experienced production engineers remain scarce.

What salary should I expect to pay Elixir developers?

Elixir is the fifth highest-paid programming language globally. In the US, junior to mid-level Elixir developers average around $117,000 per year. Senior Elixir developers average $152,000, with remote senior roles reaching approximately $163,000. These salaries reflect the extreme scarcity of the talent pool. Companies competing for Elixir talent include Discord, Pinterest, PagerDuty, and fintech firms, all of which can offer competitive compensation. For smaller companies, emphasizing interesting technical problems and open source contribution opportunities can offset a salary gap.

Do Elixir developers need to know Erlang?

Not necessarily, but it helps significantly. Elixir runs on the Erlang VM (BEAM) and interoperates seamlessly with Erlang code. An Elixir developer who understands Erlang can read OTP source code, use Erlang libraries directly, and debug at the VM level. For application-layer work (Phoenix web apps, API services), pure Elixir knowledge is sufficient. For infrastructure-level work (custom GenServers, distributed systems, performance tuning), Erlang familiarity is a strong positive signal. The strongest candidates often have contributions to both Elixir and Erlang repositories on GitHub.

Should I require Elixir experience or hire developers who can learn it?

It depends on the role. For senior positions building core infrastructure (supervision trees, distributed systems, custom OTP behaviours), prior production Elixir experience matters because the BEAM ecosystem has a steep learning curve that goes beyond syntax. For application-level Phoenix web development, strong developers from Ruby/Rails, functional programming (Haskell, Clojure, F#), or even TypeScript/JavaScript backgrounds can ramp effectively. Check GitHub for Elixir side projects as evidence of self-directed learning. The Stack Overflow survey shows 64.5% of Elixir developers came from TypeScript and JavaScript backgrounds, so the transition path is well-established.

What Elixir projects and frameworks should I look for on GitHub?

For web development: phoenixframework/phoenix and phoenixframework/phoenix_live_view. For databases: elixir-ecto/ecto. For GraphQL: absinthe-graphql/absinthe. For background jobs: sorentwo/oban. For data pipelines: dashbitco/broadway. For IoT and embedded systems: nerves-project/nerves. For numerical computing: elixir-nx/nx. For the language itself: elixir-lang/elixir. Contributors to any of these projects are working on the core infrastructure that the Elixir ecosystem depends on. Hex.pm package authors with well-maintained, widely-used libraries are also strong candidates.

How long does it take to hire an Elixir developer?

Average time-to-fill for Elixir roles ranges from 45 to 90 days, depending on seniority, location, and domain specificity. Roles requiring deep OTP expertise or distributed systems experience can take longer. The main bottleneck is the extremely small candidate pool (roughly 100,000 globally) combined with competition from companies like Discord, Pinterest, and PagerDuty that can offer top-of-market compensation. Sourcing from GitHub contribution data and community channels (ElixirForum, ElixirConf speaker lists, hex.pm package authors) can shorten this timeline by identifying candidates who are actively building but not on job boards.