Note: The job is a remote job and is open to candidates in USA. Apollo Global Management is seeking a Forward Deployed AI Engineer to support Corporate, Compliance, Legal, and Risk Management functions across the firm. This hands-on delivery role involves owning the full arc of a solution from requirements and design through build, testing, and production deployment, while working directly with business and product teams.

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 DevOps processes on Apollo's 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
• 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
• 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

Skills

• 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 lifecycle including UAT coordination, operational readiness, and post-launch support
• 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
• 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
• 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

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