The Role
Leads a team of AI engineers while designing and deploying internal AI products, agentic workflows, REST APIs, asynchronous microservices, RAG systems, and multi-agent orchestration. Builds scalable PostgreSQL and pgvector data layers, implements AI guardrails and evaluation suites, and establishes LLMOps practices including observability, prompt versioning, tracing, and latency monitoring. Partners with stakeholders to automate workflows and translate business needs into reliable AI solutions.
Summary Generated by Built In
HFM is an internationally acclaimed multi-asset broker,
delivering cutting-edge trading tools, platforms, and conditions to
traders worldwide. We are committed to innovation, transparency, and
excellence in the financial markets.
As we
continue to expand, we are seeking a driven and strategic Senior AI Engineer to join our team.
Responsibilities:
- 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.
Nice to have:
- 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++.
Resumes must be submitted in English.
Applicants must be eligible or have legal authorization to work in the country where the position is based.
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
Additional Support
- Visa
Sponsorship and Relocation Assistance
Sounds like you? Let’s
write the next chapter together!
All Applications will be handled with the strictest
confidentiality.
Skills Required
- Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
- 5+ years of backend software development experience
- 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 and multi-agent frameworks such as LangGraph, CrewAI, AutoGen, LlamaIndex, or MCP
- Experience with Docker, Kubernetes, and CI/CD
- Familiarity with LLM observability and monitoring tools
- Experience mentoring software or AI engineering teams
- Strong communication skills and full professional proficiency in English
- Product-oriented mindset and ability to build scalable internal tools and workflow automations
- Strong stakeholder management skills and ability to explain technical concepts to non-technical audiences
- AWS Certified Machine Learning Specialty or AWS Certified Solutions Architect
- Production experience with pgvector or relational data pipelines in 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 Go or C++
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
HFM is an internationally acclaimed, regulated multi-asset broker serving retail and institutional clients worldwide. The company provides online trading services and platforms across forex, contracts for difference (CFDs), futures, commodities, stocks, and indices. Its offering emphasizes competitive trading conditions, innovative tools, partner support, and access to multiple global markets through its financial technology infrastructure, helping traders participate in global markets.
