Forward Deployed AI Engineer

Role Overview Forward Deployed AI Engineer to support Corporate, Compliance, Legal, and Risk Management functions across the firm. This is a hands-on delivery role: you will own the full arc of a solution - from requirements and design through build, testing, and production deployment - working directly with business and product teams to drive outcomes in a fast-paced, regulated environment. The ideal candidate brings strong engineering fundamentals, deep practical experience with AI tools and workflows, and the maturity to operate effectively across technical and business audiences. You are comfortable taking ownership in ambiguous situations and are focused on shipping working solutions, not managing process. Key Responsibilities Delivery & Execution

• 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 DevOps processes on Azure-based platform, working within established GitOps and Flux deployment patterns
• Manage delivery across multiple concurrent workstreams, 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 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 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 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 Engineering & Delivery
• 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 DevOps practices
• Solid understanding of GitOps 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 life cycle 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
Domain & Environment
• 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
The Platform AI & Agents Axon SDK Azure AI Foundry Azure OpenAI Document Intelligence AI Search MCP broker Orchestration Temporal - agent runs, ETL pipelines, multi-step automations Data Snowflake via Delphi Event Hubs ADLS Gen2 Cosmos DB Redis EDB Postgres Cloud & Deployment Azure AKS Flux GitOps GitHub Actions Terraform central module catalog Observability Datadog Prometheus/Grafana PagerDuty ITSM & Identity ServiceNow Jira Okta (OIDC) Active Directory

The ideal candidate brings strong engineering fundamentals, deep practical experience with AI tools and workflows, and the maturity to operate effectively across technical and business audiences. You are comfortable taking ownership in ambiguous situations and are focused on shipping working solutions, not managing process., Engineering & Delivery
• 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 DevOps practices
• Solid understanding of GitOps 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 life cycle 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
Domain & Environment
• 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, Temporal - agent runs, ETL pipelines, multi-step automations
Data Snowflake via Delphi Event Hubs ADLS Gen2 Cosmos DB Redis EDB Postgres Cloud & Deployment Azure AKS Flux GitOps GitHub Actions Terraform central module catalog