GenAI & Agentic Developer

Generative Ai
United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Amazon Elastic Compute Cloud Amazon S3 Microsoft Azure Databases Continuous Integration Data Security DevOps Distributed Systems Identity and Access Management Python (Programming Language) PostgreSQL
+20 more
MongoDB MySQL NoSQL Cloud Services SQL Databases Enterprise Software Applications Retrieval-Augmented Generation Large Language Models AgentCore Agentic-AI Fastapi AI Platforms Cassandra Api Gateway Restful APIs Amazon Simple Queue Service (SQS) Terraform Prompt Orchestration Promptfoo Microservices

Job description

  • Build and maintain Back End services and APIs enabling secure access to LLM capabilities.
  • Develop and optimise Python-based GenAI & Agentic components including prompt orchestration, output validation, and evaluation tooling.
  • Integrate LLMs with enterprise systems, observability, and security frameworks.
  • Design and maintain CI/CD pipelines aligned to engineering standards (Azure DevOps primarily).
  • Collaborate closely with platform leads, architects, and SRE teams to ensure reliable operationalisation of GenAI services.
  • Support benchmarking, evaluation, and experiment tracking for LLM performance and cost.
  • Contribute to RAG implementations and data access patterns supporting enterprise use cases.
  • Help shape API standards, reusable patterns, and documentation for platform adoption.
  • Troubleshoot and optimise performance across distributed systems and cloud services., * Efficient, secure, and reusable GenAI components delivered into production.
  • Improved engineering velocity through automation and DevOps best practices.
  • Stable services, with observability and evaluation built in from day one.
  • Platform teams and application teams love using what you build.
  • Clear documentation and fast onboarding for future use cases.

Requirements

The ideal candidate will bring practical GenAI & Agentic development experience, strong automation skills, and the curiosity to solve emerging engineering challenges in this rapidly evolving space., * Strong Python Back End engineering in production systems (inc FastAPI).

  • AWS services: EC2, EKS, S3, SQS, Kenesis/Firehose, Bedrock and AgentCore.
  • Working knowledge of GenAI technologies and Large Language Models.
  • Experience evaluating LLM performance and prompt handling complexities.
  • Solid DevOps mindset with CI/CD expertise and observability best practices.
  • Comfortable working in regulated enterprise environments with strict security controls.
  • Experience integrating AI services into real-world apps or workflows.
  • Knowledge of authentication, secret management, network boundaries, and model access governance

Preferred Skills

  • Kong API Gateway, Kong Mesh, Flux CD.
  • RESTful API development (FastAPI preferred), microservices, Terraform with GitOps workflows.
  • IaC & Terraform experience with GitOps workflows.
  • Prompt redteaming & evaluation tools (like Promptfoo & Arize).
  • Experience with SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra) databases
  • Exposure to RAG patterns and vector search technologies.

Behavioural Competencies

  • Proactive self-starter who identifies gaps and drives solutions without waiting for tickets.
  • Comfortable working in ambiguous emerging domains where best practice is evolving.
  • Collaborative communicator able to influence and gain trust across engineering, data, and product teams.
  • Curiosity to explore and adopt new GenAI techniques in a structured, secure way.
  • Bias toward automating everything to reduce toil and accelerate delivery.

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