Software Engineer with AI

Job Description

Get to know us better CodiLime is a software and network engineering industry expert and the first-choice service partner for top global networking hardware providers, software providers and telecoms. We create proofs-of-concept, help our clients build new products, nurture existing ones and provide services in production environments. Our clients include both tech startups and big players in various industries and geographic locations (US, Japan, Israel, Europe). While no longer a startup - we have 250+ people on board and have been operating since 2011 we’ve kept our people-oriented culture. Our values are simple: Act to deliver. Disrupt to grow. Team up to win. The project and the team You will work on a large-scale, multi-tenant B2B commercial execution platform used by enterprise go-to-market teams. It combines cloud software, capability benchmarking and advanced analytics to turn commercial strategy into measurable action - from account planning and partner management to pricing and sales performance. This is a backend-focused Software Engineering role with a strong AI component. You'll build and operate the Python services behind the platform - APIs, data access, background processing - and you'll design and integrate the generative AI capabilities that sit on top of them: connecting LLMs with the platform's enterprise data, APIs and internal tools through prompt design, tool calling, workflow orchestration, guardrails and human review, all instrumented so that quality, latency and cost are measurable rather than assumed. Daily use of AI development tools is part of how the whole team works, not an add-on. You're expected to use assistants like Claude Code across coding, testing, debugging and code review - and to validate everything they produce before it reaches production. You'll be in regular, direct contact with product managers, designers and client-facing stakeholders, and you'll collaborate with a dedicated team of data scientists on the platform's harder analytical challenges: you own the product integration layer, they own the deeper modelling work. Security runs through everything. This is a multi-tenant SaaS platform handling sensitive enterprise client data, so every service you ship needs to respect tenant isolation, role-based access control and least-privilege data access - across the API, data and AI workflow layers. Technology stack: Backend: Python, FastAPI, Pydantic, REST, pytest Data: SQL, PostgreSQL, SQLAlchemy/async drivers, Snowflake, Redis Cloud & DevOps: Azure / AWS, Docker, Kubernetes, GitHub Actions AI: LLM APIs, prompt engineering, tool/function calling, LangChain/LangGraph, RAG, vector search (pgvector, Pinecone) AI-assisted Development: Claude Code, Codex AI observability & MLOps: LangSmith, Langfuse, Arize Phoenix, OpenTelemetry Authentication & Security: OAuth 2.0, Okta, JWT, RBAC Real-Time & Messaging: Temporal, Socket.IO / WebSockets What else you should know: Team: Product Managers, UX Designers, Fullstack Engineers, Data Engineers, DevOps Engineers, AI Engineers, Data Scientists You own the product-facing AI integration layer; deeper ML and data-science work is handled by dedicated specialists you collaborate with AI-augmented development is a core expectation of the role, not optional - daily use of tools like Claude Code or Codex across coding, testing, debugging, and code review Multi-tenant SaaS platform handling sensitive enterprise client data - a security-first mindset is expected at every layer Agile, collaborative, impact-driven environment with close cooperation with business and client-facing stakeholders Strong ownership culture and product mindset We work on multiple interesting projects at a time, so it may happen that we’ll invite you to an interview for another project if we see that your competencies and profile are well suited for it.