Senior Position
Senior AI Developer
Python
TypeScript
LLMs
AI Agents
APIs
Retrieval
Tool Calling
Multi-step Orchestration
Prompt Evaluation
AI Pipelines
Agent Frameworks
MCP
AWS Bedrock
Google Vertex AI
Azure OpenAI
Queues
Idempotency
Durable State
-
Role Overview
The Senior AI Developer will join the AI Practice and focus on building and operating production-ready AI capabilities around large language models (LLMs) and AI agents. The role is hands-on and combines software engineering, AI integration, evaluation, observability, and system design. The focus is on building reliable, scalable solutions around existing models rather than developing machine-learning models from scratch.
01
Core Responsibilities
- Design, build, deploy, and operate LLM- and agent-based features in production.
- Integrate AI models with existing systems and data through APIs, tool calling, retrieval, and multi-step orchestration.
- Design solutions with cost, latency, reliability, and scalability as key considerations.
- Build evaluation frameworks and observability capabilities to measure AI system behavior and identify changes before production release.
- Develop test sets, automated evaluation, tracing, and cost monitoring for AI-powered features.
- Design robust handling of non-deterministic AI failures, including output validation, fallbacks, degradation paths, and human-in-the-loop processes where required.
- Work with clients and product stakeholders to translate ambiguous requirements into clearly scoped and testable solutions.
- Evaluate when an LLM-based approach is appropriate and when alternative technical solutions would be more suitable.
- Apply appropriate security practices when working with AI systems, sensitive data, and third-party model providers.
- Identify and mitigate risks such as prompt injection, data leakage, and unsafe tool invocation.
02
Requirements
- Senior-level software engineering experience with Python and/or TypeScript.
- Proven experience deploying, monitoring, and maintaining production software systems.
- Hands-on experience building and deploying an LLM- or agent-based system used by users outside the development team.
- Strong understanding of how to evaluate changes to prompts, models, and AI pipelines.
- Experience working with AI systems under data security, privacy, or compliance requirements.
- Understanding of common LLM-specific risks and failure modes.
- Strong software architecture and problem-solving skills.
- Ability to work with clients and product stakeholders and translate business requirements into technical solutions.
03
Bonus / Nice to Have
- Experience with retrieval systems at scale, including hybrid search, reranking, and permission-aware or frequently changing data sources.
- Experience with agent frameworks and/or MCP.
- Experience with cloud AI services such as AWS Bedrock, Google Vertex AI, or Azure OpenAI.
- Experience designing and asynchronous and long-running systems using queues, idempotency, and durable state.
- Previous experience in a client-facing consulting environment.
04
What We Offer
- Competitive remuneration package.
- Flexible working hours.
- Fully remote working policy.
- Food and gift vouchers.
- Additional health insurance.
- 25 days paid annual leave.
- 1 additional day of leave for your birthday.
- Good work-life balance.
- Positive and collaborative working environment.
Interested in this opportunity?
Apply now and become part of our growing team.
By applying you agree to our privacy policy.
Estimated response time: 2–4 business days
We are an equal opportunity employer.