AI Engineer (Fullstack)

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 weve kept our people-oriented culture. Our values are simple:

• Act to deliver.

• Disrupt to grow.

• Team up to win.

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 hybrid Fullstack AI Engineering role. Youll turn product and design vision into shipped software with genuine depth in either front-end UI engineering or backend services and working competence in the other. Daily use of AI development tools is part of how the whole team works not an add-on.

Beyond building product features youll design and integrate generative AI capabilities that connect LLMs with the platforms enterprise data APIs and internal tools - prompt design tool calling workflow orchestration context management guardrails and human review - all instrumented so that quality latency and cost are measurable rather than assumed.

Youll be in regular direct contact with product managers designers and client-facing stakeholders and youll collaborate with a dedicated team of AI engineers and data scientists on the platforms harder analytical challenges - you own the product integration layer they own the deeper modeling work. Security runs through everything. This is a multi-tenant SaaS platform handling sensitive enterprise client data so every feature you ship needs to respect tenant isolation role-based access control and least-privilege data access across the UI API and AI workflow layers.

Technology stack:

• Frontend: React TypeScript MUI / styled-components ag-Grid amCharts Mapbox GL

• Backend: Python (FastAPI) / REST

• AI: LLM APIs prompt engineering tool/function calling LangChain / LangGraph RAG vector search (pgvector Pinecone)

• AI-Assisted Development: Claude Code Codex or similar AI coding assistants

• AI observability: LangSmith Langfuse Arize Phoenix OpenTelemetry

• Data: PostgreSQL SQL Snowflake Redis

• Authentication & Security: OAuth 2.0 Okta JWT RBAC

• Cloud & DevOps: AWS / Azure Docker Kubernetes GitHub Actions

• Real-Time & Messaging: Temporal / WebSockets

What else you should know:

• Team: Product Managers UX Designers Fullstack Engineers Data Engineers DevOps Engineers AI Engineers Data Scientists client-facing stakeholders

• 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 across 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 well invite you to an interview for another project if we see that your competencies and profile are well suited for it.

As a part of the project team you will be responsible for:

• Developing features across the full stack with strong expertise in either React/TypeScript UI or Python (FastAPI)/ services and working knowledge of the other

• Working with Product Managers and Designers to turn product requirements and designs into production-ready software

• Owning features end to end: from first implementation through release instrumentation and iteration based on how the feature is actually used

• Building and integrating generative AI features that connect LLMs with the platforms enterprise data APIs and internal tools - prompt design tool calling workflow orchestration context management guardrails and human review

• Evaluating AI workflows and monitoring quality latency cost and failure rates

• Using AI coding assistants effectively while validating all generated output before it reaches production and helping build automated quality gates

• Participating in code reviews identifying architectural and AI reliability risks and improving engineering practices

• Documenting data flows API contracts and AI workflow behavior clearly enough for non-engineers to act on

• Writing and optimizing SQL against PostgreSQL and contributing to schema and data-model decisions

• Applying security-first thinking at every layer including tenant isolation role-based access control and least-privilege data access across UI API and AI workflows

As an AI Engineer you must meet the following criteria:

• 6 years of professional experience in fullstack web development

• Strong experience in either: React / TypeScript UI engineering or Python (FastAPI) / backend development

• Hands-on experience integrating LLM APIs into production applications including prompt design tool/function calling and safe handling of non-deterministic output

• Experience using AI coding assistants such as Claude Code Codex or similar on a daily basis

• Strong SQL and relational database knowledge preferably PostgreSQL

• Experience with APIs authentication authorization and technologies such as OAuth 2.0 JWT and RBAC

• Understanding of multi-tenant SaaS application security

• Experience with Docker and Kubernetes

• Ability to evaluate AI features and monitor quality latency cost and reliability

• Product mindset and ownership - you identify problems propose solutions and take features from idea to production

• Strong communication skills and good knowledge of English (minimum C1 level)

Beyond the criteria above we would appreciate the following nice-to-haves:

• LLM evaluation and observability tools such as LangSmith Langfuse Arize Phoenix or OpenTelemetry

• Knowledge of prompt optimization and evaluation techniques

• Agentic workflows multi-step orchestration guardrails and human-in-the-loop patterns

• RAG and vector search e.g. pgvector or Pinecone

• LangChain or LangGraph

• Experience with Snowflake or a comparable cloud data warehouse

• Temporal / WebSockets Redis pub/sub

• Flexible working hours and approach to work: fully remotely in the office or hybrid

• Professional growth supported by internal training sessions and a training budget

• Solid onboarding with a hands-on approach to give you an easy start

• A great atmosphere among professionals who are passionate about their work

• The ability to change the project you work on