Generative AI Engineer

Title- Senior Software Developer Location- Plano TX, 3 DAYS/ WEEK, Hybrid, Onsite We need strong candidates who have developed LLM’s, Designed workflows and AI tools deployment knowledge. This role offers the opportunity to lead in cutting-edge automated software modernization driven by GenAI and platform engineering standards. Join a horizontal engineering team supporting 600+ application teams on a mission to raise engineering maturity by driving standards, guidelines, platform capabilities, and large-scale technical debt remediation. You will build advanced agentic AI workflows to automatically analyze codebases, detect tech debt, and generate high-quality fixes—from vulnerability patches to dependency and language upgrades. This is a hands-on, high-impact role shaping the future of automated software modernization. Required Skills: • Deep knowledge of multi-agent architectures including planners, executors, and tool routing. • Strong understanding of RAG systems: chunking, embeddings, vector/hybrid search, and retrieval policies. • Experience evaluating LLMs and agent workflows incorporating statistical reasoning and validation. • Proficiency with AWS (Lambda, ECS/EKS, S3, API Gateway, EC2, IAM) and Infrastructure-as-Code for cloud resource automation and deployment. • Experience with observability tools (Datadog, logging, tracing, metrics). • Familiarity with PostgreSQL, DBT, data modeling, schema evolution, and performance tuning. • Hands on experience on AI • AI Engineer who has extensive knowledge on LLM creation, AI tool adoption and also defining the frameworks • should be strongly vocal enough to communicate with the customers MUST HAVE Qualifications: Platform runs on AWS and AWS knowledge is must. • 5+ years experience building production-grade systems with end-to-end ownership. • Expertise in Python programming, software engineering best practices, testing strategies, CI/CD, and system design. • Hands-on experience shipping LLM-powered features such as autonomous workflows or function calling with measurable impact on reliability or latency. • Deep knowledge of multi-agent architectures including planners, executors, and tool routing. • Strong understanding of RAG systems: chunking, embeddings, vector/hybrid search, and retrieval policies. • Experience evaluating LLMs and agent workflows incorporating statistical reasoning and validation. • Proficiency with AWS (Lambda, ECS/EKS, S3, API Gateway, EC2, IAM) and Infrastructure-as-Code for cloud resource automation and deployment. • Experience with observability tools (Datadog, logging, tracing, metrics). • Familiarity with PostgreSQL, DBT, data modeling, schema evolution, and performance tuning. • Knowledge of vector databases like Pinecone or pgvector. • Experience building or optimizing CI/CD pipelines (GitHub Actions or similar). • Proven track record in application modernization, dependency management, and technical debt reduction. • Ability to rapidly prototype, validate, and transition solutions to production systems. Preferred Skills: • Experience designing agent infrastructure with sandboxing, tool isolation, and fail-safe execution. • Background in large-scale platform engineering or developer experience tooling. • Understanding of security, compliance, and privacy for enterprise AI systems. • Strong architectural communication ability, including RFC writing and diagramming. Attributes: • Adaptable and proactive problem solver. • Strong ownership mindset with excellent collaboration and communication skills. • Comfortable in ambiguous, fast-paced R&D environments. • Passionate about building high-leverage platform capabilities impacting hundreds of engineering teams.