Principal Technology Architect - LLMs, agentic coding systems, intelligent IDEs, AI
Role
Senior Forward Deployed Engineer (AI Native) - Principal Technology Architect
Location: London
Compensation: Competitive (including bonus)
Responsibilities
- Serve as principal engineering lead for complex, multi region AI programs; define solution strategy, roadmap, and measurable outcomes.
- Lead workshops and discoveries focused on AI enabled engineering (LLMs, agents, RAG, prompt ops, model ops).
- Architect AI integrations across APIs, pipelines, cloud services, and enterprise toolchains; enforce reliability, safety, and cost discipline.
- Operationalize agentic engineering (task decomposition, tools, memory, planning) for accelerated delivery.
- Build and mentor high performing teams; cultivate experimentation, reusable assets/accelerators, and continuous learning.
- Govern delivery (scope, risk, quality), communicate crisply with executives and technical stakeholders, and course correct proactively.
Required
Technology
- 15+ years of progressive software engineering; 5+ years leading AI native solutions at enterprise scale.
- Hands on with LLMs and agentic frameworks; design and deploy AI systems that augment SDLC (requirements coding testing ops).
Tooling & Platforms (practitioner proficiency)
- Claude Code (Anthropic) for secure, context rich code assistance; use with projects, tool use, code planning.
- Google Gemini (Nano/Pro/1.5) for multimodal reasoning; integrate via Vertex AI; grounding, structured output, function calling.
- Azure OpenAI / GPT 4.x for enterprise LLM services; model selection, limits, rate management, content filters/AI safety.
- Amazon Q for developer and ops assistance across AWS stacks.
- Cursor, GitHub Copilot, Devin for IDE native agentic coding; policies for context windows, secrets hygiene, and traceability.
- NotebookLM/Gemini for research workflows where permitted; govern enterprise knowledge ingestion.
Architecture & Integration
- Distributed systems, microservices, cloud native (Azure/AWS/GCP); secure API design (REST/GraphQL).
- MLOps & AIOps: CI/CD for AI, model lifecycle (eval, versioning, rollout/rollback), guardrails, telemetry, drift monitoring, prompt safety.
- DevSec & Responsible AI: Privacy by design, PII handling, secrets management, policy enforcement, human in the loop approvals, auditability.
- Languages: Advanced Python plus one of Java/TypeScript/Go; containerization (Docker/K8s).
Leadership & Communication
- Executive presence: influence C suite decisions with crisp, data backed narratives.
- Lead distributed teams across geographies/time zones; resolve conflicts and drive outcomes.
- Pre sales/solutioning for AI transformation; quantify value (cycle time, defect rate, throughput, cost to serve).
Preferred
- Delivery leadership for Fortune 500 AI programs; published thought leadership or patents.
- Proven track in building accelerators (prompt libraries, agent frameworks, governance kits), and running bake offs/benchmarks across LLMs.
- Experience establishing enterprise AI enablement: policy, templates, blueprints, playbooks, COPs.
Personal
- High analytical skills
- A high degree of initiative and flexibility
- High customer orientation
- High quality awareness
- Excellent verbal and written communication skills
Equal Opportunity Employment
All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer