Coforge
Artificial Intelligence Engineer
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Job Title: AI Engineer
Job Location: London, UK
Job Type: Fulltime
Exp: 2+ Yrs
We at Coforge are hiring for Agentic AI Engineer role with the following skillset
Role Purpose
Design, develop, test, and deploy AI-agent workflows that use language models, enterprise data, APIs, and tools to complete business tasks safely and efficiently.
Key Responsibilities
- Convert business requirements into agent workflows, decision logic, tool calls, and human approval steps.
- Build single-agent and basic multi-agent solutions.
- Develop prompts, structured outputs, routing, retries, memory, and exception handling.
- Implement RAG, grounding, vector search, and context management.
- Integrate agents with APIs, databases, enterprise applications, and workflow platforms.
- Test accuracy, task completion, safety, latency, cost, and hallucination risk.
- Implement guardrails for privacy, permissions, prompt injection, and responsible AI.
- Diagnose issues using logs, traces, model responses, and tool-call history.
- Develop maintainable Python or TypeScript code and support CI/CD deployment.
- Create technical documentation, workflow diagrams, and operational runbooks.
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Required Skills
- Python and/or TypeScript
- Generative AI, large language models, prompt engineering, and structured outputs
- Agent frameworks such as LangGraph, Semantic Kernel, AutoGen, or CrewAI
- RAG, embeddings, vector databases, and enterprise search
- REST APIs, SQL, Git, Docker, cloud services, and CI/CD
- AI evaluation, monitoring, security, and responsible-AI practices
Qualifications
- Bachelor’s degree in Computer Science, Engineering, IT, Data Science, or equivalent experience.
- 2–5 years in software, data, automation, or AI engineering.
- Experience building at least one generative-AI, RAG, chatbot, automation, or agentic-AI solution.
- Experience integrating applications through APIs.
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Behavioural Competencies
- Strong problem-solving and analytical skills
- Experimentation and continuous-learning mindset
- Good engineering and documentation discipline
- Ability to collaborate with technical and business teams
- Ownership of development, deployment, and issue resolution
- Sound judgement when handling AI risks and limitations
Performance Measures
- Agent accuracy and task-completion rate
- Business adoption and productivity improvement
- Reliability, latency, and cost efficiency
- Defect and hallucination rates
- Delivery against sprint and release commitments
- Code quality, test coverage, and documentation
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