• Embed with customer teams to translate business problems into production AI architectures spanning models, data, application, and operations — owning the outcome end to end.
• Design, build, and deploy LLM-powered applications — including RAG pipelines, agentic workflows, and orchestration frameworks — integrated with client data stores, APIs, and security controls.
• Stand up the AWS and Google Cloud environments needed for AI services — enabling and configuring Amazon Bedrock, SageMaker, Google Vertex AI, and related resources (IAM roles, networking, model access, and service quotas) self-sufficiently within client guardrails, partnering with dedicated cloud engineers for deeper foundational account and landing-zone setup.
• Drive enterprise adoption of agentic developer tooling (Anthropic Claude Code, OpenAI Codex, AWS Kiro): secure rollout, identity and tenant isolation, SDLC and CI/CD integration, and the developer enablement that turns licenses into measurable productivity.
• Lead adoption and change management — build golden-path templates, enablement assets, and team workflows so AI solutions and tools are genuinely used, not merely delivered.
• Define and instrument success — adoption, business impact, and ROI metrics — and iterate post-launch until targets are met.
• Rapidly prototype proofs-of-concept and iterate them into production-grade systems alongside the customer.
• Establish reusable accelerators, reference implementations, and AI delivery harnesses applicable across engagements.
• Champion shift-left security, responsible AI, and FinOps practices for AI workloads, including token-cost and model-routing discipline.
• Mentor engineers during build and deployment; troubleshoot complex issues spanning models, infrastructure, application, and data layers.
• Serve as an escalation point during go-live and hyper-care.
• Support pursuit teams with solution diagrams, scoping, and engagement estimation.
• Present technical vision and adoption strategy to C-suite and enterprise architects.
• Publish blog posts, white papers, and internal knowledge articles.