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Hybrid role requiring three days per week on-site in Menlo Park.
Join The Ai Research & Solutions Group
As a Senior Software Engineer in the AI Research & Solutions group, you will be a seasoned contributor building the core systems that power enterprise AI agents. You'll work hands-on developing agentic applications—the software that allows AI to reason, act, and integrate with complex enterprise environments. We're actively exploring Elixir/OTP as a foundation for our agent infrastructure, drawn to its strengths in concurrency, fault-tolerance, and distributed systems. You'll help shape our technical direction and drive key initiatives independently.
This role is ideal for engineers who love building systems that think, connect, and abstract complexity—whether your background is in traditional software engineering, academic research, or a quantitative discipline where you learned to express complex ideas in clean code.
Key Responsibilities
1. Agentic Application Development
Build Agent Components: Design and implement production-grade components for AI agents—tools, orchestration logic, memory systems, and integrations with enterprise data sources. You may work with Elixir/OTP (GenServers, Supervisors, Phoenix) as we evaluate it for our agent infrastructure.
Quality & Reliability: Own the quality of your deliverables, writing robust, well-tested code that operates reliably in production environments.
Performance Optimization: Profile and optimize agent behavior, API latencies, and resource consumption to meet enterprise-scale demands.
2. Integration & Systems Thinking
Bridge Systems: Develop connective tissue between AI agent backends and the OutSystems low-code platform, ensuring seamless data flow and secure API contracts.
Abstraction Design: Contribute to the design of software abstractions that enable agents to reason about and interact with complex legacy systems and modern architectures alike.
Cross-Functional Delivery: Collaborate with researchers, product managers, and platform engineers to translate requirements into working solutions.
3. Mentorship & Technical Growth
Mentor Junior Engineers: Support the growth of engineers through code reviews, pairing sessions, and knowledge sharing.
Continuous Learning: Stay current with advances in agentic AI, LLM orchestration frameworks, and systems engineering practices.
Documentation: Contribute to internal best practices, architecture decision records, and onboarding materials.
Required Skills & Experience
Technical Expertise (The Must-Haves)
Software Engineering Foundation: 5+ years of experience building production software, with demonstrated ability to own and deliver complex features end-to-end.
Python Proficiency: Strong hands-on experience with Python; ability to write clean, maintainable, and performant code.
AI/ML Systems Exposure: Practical experience working with LLMs, AI agents, or ML systems—whether in industry, research, or open-source projects.
API & Integration Skills: Experience designing and consuming REST/gRPC APIs; understanding of distributed systems patterns (queues, event-driven architectures, microservices).
Cloud-Native Familiarity: Working knowledge of containerization (Docker), orchestration (Kubernetes), and cloud platforms (AWS, Azure, or GCP).
Strongly Preferred
Elixir/OTP Experience: Hands-on experience with Elixir and OTP patterns—GenServers, Supervisors, Applications, and Phoenix. We're evaluating Elixir for our agent infrastructure and would value someone who can help us make informed architectural decisions.
Background Flexibility (We Value Diverse Paths)
Academic Contributors Welcome: We value candidates from research backgrounds—whether you completed a PhD, contributed to open-source projects during your studies, or built software to support your research in mathematics, physics, philosophy, or computational sciences.
Abstraction Thinkers: If you've written code that models complex systems—whether that's physics simulations, formal logic systems, or distributed algorithms—we want to hear from you.
Desirable Expertise (Nice-to-Have)
Network Programming: Experience with low-level network code, forwarding plane implementations, packet processing, or socket programming.
Functional Programming: Experience with functional languages (Elixir, Erlang, Haskell, OCaml, F#) and their approaches to concurrency and reliability.
LLM Orchestration: Hands-on experience with LangChain, Semantic Kernel, or similar agent orchestration frameworks.
OutSystems or Low-Code Platforms: Familiarity with OutSystems or similar platforms and their integration patterns.
Who You Are
Systems Thinker: You understand how software systems fit together and can reason about data flow, state management, and failure modes.
Concurrency-Aware: You've thought deeply about building reliable, concurrent systems—whether through actor models, event-driven architectures, or other approaches.
Independent Driver: You take ownership of problems and drive them to completion with minimal hand-holding.
Collaborative Builder: You communicate clearly, give and receive feedback constructively, and enjoy working in a team that values both research and delivery.
Curious & Adaptable: You're excited by new problems, comfortable with ambiguity, and eager to learn new domains—including new languages and paradigms.
Why This Role?
This is an opportunity to work at the intersection of AI research and enterprise software delivery. You won't just be maintaining existing systems—you'll be building the next generation of agentic applications and helping shape our technical direction, including evaluating technologies like Elixir/OTP for building reliable, concurrent agent infrastructure.