Technical Lead - AI Engineering & Autonomous SDLC Platform

Role: Technical Lead - AI Engineering & Autonomous SDLC Platform

Location: Richardson, TX(Hybrid)

Duration: Long Term Contract

Role Summary

• We are looking for a hands-on Technical Lead who understands how enterprise systems work, can define clear system designs, and can guide end-to-end SDLC delivery for an AI-enabled engineering platform. The role will lead technical execution for agentic workflows, skills, orchestration, shared memory, audit controls, quality gates, and DevOps integrations while also contributing as an individual hands-on engineer.
• We are looking for a hands-on Technical Lead who can independently drive solution discussions, lead technical conversations with stakeholders, and actively contribute to implementation. This is n ot a pure architecture or people management role. The ideal candidate is a strong individual contributor who understands how systems work end-to-end, can design practical solutions, and is comfortable building, debugging, and deploying AI-enabled workflows and platforms.
• The individual will lead technical direction for an AI-enabled SDLC platform involving agent orchestration, workflow automation, memory management, governance controls, quality gates, and enterprise tool integrations while remaining actively engaged in coding and delivery activities. The platform includes planning, design, development, code review, testing, security, and release workflows orchestrated through AI agents

Key Responsibilities

• Own technical design for AI-enabled SDLC workflows covering planning, design, coding, code scanning, review, testing, performance validation, and release stages.
• Define agent roles, execution patterns, handoffs, artifacts, retry loops, human review gates, audit trails, and operational controls.
• Build and integrate agent orchestration, shared memory, audit trails, governance controls, and human review gates.
• Establish reusable engineering patterns for context memory, project memory, session memory, workflow state, and traceability.
• Guide integration with Jira, Azure DevOps, GitHub, CI/CD tools, cloud services, code repositories, and enterprise delivery platforms.
• Partner with program leadership, product stakeholders, architects, security, DevOps, and engineering teams to align scope, risks, and delivery priorities.
• Contribute directly to platform development through hands-on coding, debugging, testing, and deployment activities.
• Support pilot execution by validating selected SDLC scenarios from end to end and refining the scale roadmap based on results.

Required Qualifications

• 12+ years of software engineering experience.
• 3+ years of experience acting as a Technical Lead, Lead Engineer, or Principal Engineer.
• Strong understanding of end-to-end SDLC, including design, development, testing, deployment, and production support.
• Proven experience designing and delivering cloud-native applications on AWS.
• Strong system design knowledge with the ability to explain application, integration, data, and deployment architecture.
• Experience leading technical discussions directly with customers and business stakeholders.
• Ability to work independently with minimal oversight and drive technical execution.
• Strong communication skills with ability to explain technical design, delivery risks, dependencies, and trade-offs to program and engineering stakeholders.

AI and Agentic Engineering Skills

• Experience building LLM-enabled applications, custom AI skills, tools, agents, and workflow automations.
• Working knowledge of agent orchestration frameworks such as LangGraph, LangChain, CrewAI, or similar agent workflow platforms.
• Understanding of RAG, embeddings, vector databases, prompt engineering, tool calling, guardrails, observability, and AI governance patterns.
• Ability to debug agent failures, state transitions, prompt/tool issues, context quality, hallucination risk, and workflow bottlenecks.

Technical Skills

• Backend: Python, FastAPI, REST APIs, microservices, event-driven patterns
• Frontend: React.js, TypeScript, Next.js, workflow dashboards
• Cloud/Ops: AWS, ECS, Lambda, API Gateway, S3, DynamoDB, Docker, CI/CD, GitHub Actions, Azure DevOps, monitoring and logging.

Preferred Profile

• Strong individual contributor first, technical leader second.
• Can independently own a problem from discovery through production deployment.
• Comfortable leading client conversations, whiteboarding solutions, and then implementing them.
• Strong analytical and troubleshooting mindset.
• Capable of balancing architecture, coding, debugging, and delivery execution.
• Thrives in fast-paced environments where ownership and hands-on execution are equally important.
• Able to convert ambiguous business objectives into working technical solutions with minimal supervision

Success Profile for This Engagement

The right candidate should be able to:

• Lead solutioning discussions with stakeholders.
• Design the end-to-end workflow and technical approach.
• Build and debug AI agents, skills, and orchestration flows.
• Contribute at least 50-70% hands-on engineering effort.
• Drive pilot delivery from design through production validation.
• Operate with minimal dependency on architects or additional technical leadership while ensuring successful delivery of the AI-enabled SDLC platform.