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