Senior AI Engineer
- Mentor a team of 3 AI Engineers, guiding technical architecture, code quality, sprint delivery, and skill development for internal AI initiatives.
- Design and deploy internal AI products and agentic workflows using a hybrid stack of custom microservices (FastAPI) and managed services (Amazon Bedrock AgentCore).
- Develop high-performance REST APIs and asynchronous microservices in FastAPI to orchestrate agent execution, connect internal tools, and handle real-time data flow.
- Architect scalable data layers and persistent state stores utilizing PostgreSQL and pgvector for agent memory, transactional records, and enterprise retrieval.
- Build and optimize multi-agent orchestration systems leveraging task decomposition, state management, tool integrations via Model Context Protocol (MCP), and structured reasoning.
- Partner cross-functionally with internal stakeholders and department heads to identify operational bottlenecks and translate business requirements into high-impact AI automations.
- Implement robust AI guardrails and evaluation suites (using Bedrock Guardrails, schema validation, and latency/accuracy telemetry) to guarantee safe and reliable internal agent execution.
- Establish LLMOps standard practices, including RAG pipeline tuning, prompt versioning, OpenTelemetry tracing, and latency monitoring across custom microservices and AWS infrastructure.
Requirements
- Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
- 5+ years of backend software development experience, including 3+ years building and deploying LLM and agentic AI applications.
- Strong proficiency in Python, FastAPI, PostgreSQL (including pgvector), and AWS.
- Experience with Amazon Bedrock AgentCore, multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen, LlamaIndex, MCP), Docker, Kubernetes, and CI/CD.
- Familiarity with LLM observability and monitoring tools (e.g., OpenTelemetry, LangSmith, Phoenix, CloudWatch).
- Proven experience mentoring software/AI engineering teams.
- Strong communication skills and full professional proficiency in English.
- Product-oriented mindset with the ability to build scalable, user-focused internal tools and workflow automations.
- Strong communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
- AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect.
- Experience using pgvector or relational data pipelines in production RAG systems.
- Experience building internal developer platforms, enterprise workflow automation, or administrative AI assistants.
- Familiarity with FinTech platforms, FX trading, or financial services operations.
- Knowledge of systems languages such as Go or C++.
Applicants must be eligible or have legal authorization to work in the country where the position is based.
Benefits
- Hybrid
Work Model (2 days working from home)
- Monthly
Wolt Vouchers
- Comprehensive
Health & Life Insurance
- Provident
Fund (Upon completion of the trial period)
- Summer
Short Fridays (August)
- Additional
Paid Annual Leave (up to 30 days, based on years of
service)
- Birthday
Leave
- Training
& Education Allowance
- Udemy
Business access
- Gym
Membership
- Referral
Bonus Program
- Visa
Sponsorship and Relocation Assistance