Job Description
Software Engineering & Delivery:
• Design, Build, and ship production quality services within our current business controls
• Build and Optimise DecOps pipelines - enhancing CI/CD processing, including testing and platform/process observability
• Design, iterate, and optimise prompts for a wide range of LLM use cases — instruction following, structured output generation, classification, summarisation, code generation, and reasoning tasks
• Build and manage prompt libraries and versioning strategies, treating prompts as first-class engineering artefacts
• Collaborate with product and domain teams to translate business requirements into precise, well-structured prompt specifications
Agentic AI & LLM Integration:
• Architect and implement /maintain agentic systems — autonomous agents, multi-agent pipelines, tool-use workflows, planning loops, and memory-augmented reasoning
• Implement LLM observability — logging, tracing, evaluation pipelines, and guardrails — to maintain quality and reliability in production AI systems
• Advise on responsible AI deployment, including output validation, human-in-the-loop design, and risk mitigation for agentic workflows
Technical Skills & Experience
Full-Stack Engineering:
• Strong proficiency in Java / Spring Boot — REST APIs, event-driven services, security, and performance optimisation
• Solid React development skills and API integration
• Experience with relational and in memory databases (PostgreSQL, Redis)
• Messaging and streaming platforms — Kafka, or equivalent
Prompt Engineering:
• Demonstrable, hands-on experience engineering prompts for production LLM applications — not just prototypes
• Familiarity with prompt evaluation frameworks and tooling (PromptFlow, LangSmith, Braintrust, or custom eval pipelines)
• Understanding of tokenisation, context limits, temperature tuning, and model-specific behaviours across major LLM providers
• Experience structuring prompts for tool/function calling, structured JSON output, and multi-turn conversations
DevOps & Infrastructure:
• Kubernetes — deployments, services, ingress, Helm, Kustomize, HPA, and RBAC
• CI/CD pipelines — GitHub Actions, GitLab CI, Jenkins, or equivalent
• Infrastructure as code — Terraform
• Cloud platforms — AWS, GCP, or Azure
Engineering Tech Lead in Sheffield employer: Infosys Pontoon
As a Service Manager within the Markets, Intelligence and Enforcement (MIE) Product Group, you will thrive in a dynamic work culture that prioritises operational excellence and innovation. Our commitment to employee growth is evident through continuous training opportunities and a collaborative environment that encourages knowledge sharing and professional development. Located in a vibrant area, we offer a unique blend of competitive benefits and a supportive team atmosphere, making us an exceptional employer for those seeking meaningful and rewarding careers in IT service management.
