Technical Lead - Operation AI/ML Enablement | Onsite - Delaware

Key Responsibilities 

• Own delivery of LLM API integration and SDK patterns used across applications. 

• Set organizational guidance on which LLM to use for what use case and drive delivery of multi-LLM scenarios. 

• Define standards for advanced prompt engineering and context window management. 

• Own delivery of RAG systems, including vector database selection/topology and knowledgebase design. 

• Drive delivery of AI agent and multi-agent systems and tool-use/MCP integration patterns. 

• Own guardrails delivery (safety, compliance, PII handling in prompts/outputs) — critical in a financial-services context. 

• Define evaluation frameworks and real-time eval strategy; set standards for AI testing in CI/CD. 

• Own latency profiling, AI observability, and cost tracking/management for LLM-backed systems. 

• Run day-to-day delivery of the offshore development team: sprint commitments, code/design review, real-time unblocking, and hands-on work on critical-path AI features. 

• Report delivery status, risks, and blockers to engineering leadership. 

Must-Have Qualifications 

• 6+ years in software engineering, with 2+ years as a tech lead owning end-to-end delivery of LLM/AI-powered systems (not a pure design/review architect role). 

• Proven track record of shipping AI-powered features on committed timelines, including hands-on troubleshooting under delivery pressure. 

• Strong, hands-on Python skills at an architectural/systems level. 

• Proven experience architecting LLM API integrations and SDK-level abstractions across multiple providers. 

• Demonstrated judgment on model selection (cost, latency, capability trade-offs) across use cases. 

• Deep expertise in prompt engineering and context window management at scale. 

• Proven design experience with RAG systems, including vector database architecture and knowledgebase design. 

• Experience architecting AI agents/multi-agent systems and tool-use patterns (MCP or equivalent). 

• Strong understanding of guardrails design — content safety, PII protection, compliance controls for AI outputs. 

• Experience defining evaluation frameworks and integrating AI testing into CI/CD. 

• Proven ability to design for latency, observability, and cost management of AI systems in production. 

• Financial-services or regulated-industry experience strongly preferred given compliance/guardrail stakes. 

• Strong stakeholder communication; able to directly manage day-to-day delivery of an offshore team (standups, unblocking, sprint accountability). 

Nice-to-Have Qualifications 

• Direct experience with specific frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). 

• Experience with AWS Bedrock or comparable managed LLM platforms. 

• Contributions to or deep familiarity with MCP (Model Context Protocol) implementations. 

• Experience building internal LLM gateways. 

• Familiarity with responsible-AI/model-risk-management frameworks used in financial services.

Compensation, Benefits and Duration

Minimum Compensation: USD 56,000
Maximum Compensation: USD 196,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post