Senior Full Stack GenAI Engineer

Position: Senior Full Stack GenAI Engineer Location: Plano, TX (Hybrid) Duration: 6 Months to start with Description: This position will require export control form. The hiring manager is looking forward to onboard Senior Full Stack Gen AI Engineer, someone who has all the experience of working with building software, deploying applications, hands on with Python/JAVA, creating CI/CD pipelines, experience with modern architecture styles: microservices, APIs. The team will be working on current projects, business applications, responsible for influencing the platform, AI testing framework (RAGAS, DeepEval). Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock) Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex) Full Stack Experience - 5-6 years, Gen AI Framework and Tool - 3 years. Total experience 10 years. AWS - Highly preferred. 6-12 months months contract with possibility of extension/conversion. This will be a hybrid position (3 days in office Tue -Thu), please submit local candidates. Interview Process: 1st Round- MS Teams - 1st round Technical Screening 30 Minutes 2nd Round - Onsite - 1 hour, might include coding as well. Who we are Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at client. As one of the world's most admired brands, client is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We're looking for diverse, talented team members who want to Dream. Do. Grow. with us. What we're looking foris seeking a Senior GenAI Engineer Initiatives to drive the design of secure, scalable, and modern applications, with a strong emphasis on AI and GenAI-enabling technologies. This is a senior-level individual contributor role within the Architecture organization, focused on delivering hands-on solution designs and proofs of concept that bring innovative ideas to life. You will work closely with Domain Architects, product teams, and engineers to solve real business problems by developing good scalable GenAI Solutions. What you'll be doing Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval-augmented generation (RAG). Fine-tune foundation models using domain-specific data. Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF). Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools. Implement responsible AI practices including bias detection, hallucination mitigation, and explainability. Monitor and optimize model performance, latency, and cost. Use techniques like quantization, distillation, and caching to improve efficiency. Stay ahead of GenAI trends and emerging technologies. Drive experimentation with new models, agents, and frameworks (e.g., LangChain, LlamaIndex, OpenAI, Anthropic, etc.). Ensure compliance with data privacy, security, and regulatory standards. Evaluate and select appropriate model types (open-source vs proprietary) based on business needs. Lead hands-on solution evaluations, prototypes, and proofs of concept, especially for initiatives involving AI, GenAI, and emerging technologies Make informed architectural trade-offs based on business needs, performance, cost, and long-term maintainability Contribute reusable patterns and documentation that support solution delivery across teams Stay informed on trends in cloud services, architecture frameworks, and GenAI tooling. Full Stack 5 years - Java/Python, CI/C pipelines must Atleast 2 years should be with Gen AI tools and framework. AWS - Must Requirements: Qualifications/ What you bring (Must Haves) - Highlight Top 3-5 skills 10 years of software engineering and development experience Proven experience in building and deploying GenAI applications in production. Strong programming skills in Python/JAVA and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face, etc.). Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Familiarity with CI/CD for ML workflows and versioning tools like MLflow or DVC. Knowledge of prompt engineering, few-shot learning, and agent-based systems. Hands-on experience designing and building cloud-native solutions (preferably on AWS) Experience with modern architecture styles: microservices, APIs, event-driven systems Strong ability to articulate technical solutions, trade-offs, and system behavior to both technical and non-technical stakeholders Added bonus if you have (Preferred): Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock) Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex) AWS AI certification Financial Services experience #TB_IT

Created: 2026-03-04