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Forward Deployed Engineer; Azure​/DevOps​/AI

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Mphasis
Full Time position
Listed on 2026-07-09
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), DevOps, Azure
Salary/Wage Range or Industry Benchmark: 70000 - 90000 GBP Yearly GBP 70000.00 90000.00 YEAR
Job Description & How to Apply Below
Position: Forward Deployed Engineer (Azure/DevOps/AI)
Location: Greater London

Responsibilities

  • Lead end-to-end solution delivery across Corporate, Compliance, Legal, and Risk Management domains — from design and build through UAT and production deployment
  • Own release readiness: manage UAT-to-production transitions, validate operational quality, and ensure solutions meet the firm’s engineering and compliance standards
  • Build and maintain CI/CD pipelines and Dev Ops processes on Apollo’s Azure-based platform, working within established Git Ops and Flux deployment patterns
  • Manage delivery across multiple concurrent work streams, coordinating with engineering, product, and business teams to maintain momentum and remove blockers
AI-Enabled Solution Design & Build
  • Apply AI tools, agent frameworks, and workflow orchestration to solve business-critical problems — selecting the right approach and model for each use case rather than defaulting to the most complex solution
  • Design and implement agent workflows on Apollo’s Axon SDK and Azure AI Foundry, integrating Azure OpenAI, Document Intelligence, and AI Search
  • Build multi-step automations and AI pipelines using Temporal as the firm’s enterprise workflow orchestrator
  • Integrate solutions with Apollo’s data platform — consuming Snowflake data through the Delphi data PaaS, connecting to operational systems, and working within the firm’s data governance model
  • Expose and consume capabilities through Apollo’s internal Model Context Protocol (MCP) broker pattern
Stakeholder Engagement
  • Work directly with business leads, product managers, and domain teams to gather requirements, shape use cases, and translate them into clear, deliverable technical solutions
  • Communicate progress, risks, and trade-offs clearly to both technical leads and senior business stakeholders
  • Contribute to solution documentation, runbooks, and knowledge transfer as a standard part of delivery
Required Skills & Experience
  • Proven track record of end-to-end solution delivery in production enterprise environments — design through deployment and ongoing operation
  • Strong hands-on experience with Azure: AKS, Azure AI services, CI/CD pipeline implementation, and Dev Ops practices
  • Solid understanding of Git Ops deployment patterns and Flux-based release workflows
  • Experience writing infrastructure configuration — Terraform or equivalent IaC — in a team-managed environment
  • Comfortable working across the full delivery lifecycle including UAT coordination, operational readiness, and post-launch support
AI & Automation
  • Deep practical experience with AI development workflows: agent design, prompt engineering, workflow orchestration, and model selection
  • Hands-on experience with AI frameworks and orchestration tools — applied to real delivery problems, not proof-of-concept work
  • Fluency with AI-assisted development tooling (Cursor, Claude, Codex) as a primary accelerant for engineering delivery
  • Working knowledge of Azure AI Foundry, Azure OpenAI, Document Intelligence, and AI Search is strongly preferred
  • Experience with Temporal or a comparable workflow orchestration platform is a plus
  • Exposure to Corporate, Compliance, Legal, or Risk Management functions; understanding of the domain accelerates delivery significantly
  • Strong communication and stakeholder management skills; ability to operate credibly at both working and senior levels
  • Ownership mindset, high accountability, and the flexibility to meet delivery commitments in a demanding environment
Observability
  • Datadog
  • Prometheus / Grafana
  • Pager Duty
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