Senior Full Stack GenAI Engineer

An International company, located in Plano, TX is seeking a Senior GenAI Engineer

for a 6+ month contract role.

o Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval-augmented generation (RAG).

o Fine-tune foundation models using domain-specific data.

o Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF).

o Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools.

o Implement responsible AI practices including bias detection, hallucination mitigation, and explainability.

o Monitor and optimize model performance, latency, and cost.

o Use techniques like quantization, distillation, and caching to improve efficiency.

o Stay ahead of GenAI trends and emerging technologies.

o Drive experimentation with new models, agents, and frameworks (, LangChain, LlamaIndex, OpenAI, Anthropic, etc.).

o Ensure compliance with data privacy, security, and regulatory standards.

o Evaluate and select appropriate model types (open-source vs proprietary) based on business needs.

o Lead hands-on solution evaluations, prototypes, and proofs of concept, especially for initiatives involving AI, GenAI, and emerging technologies

o Make informed architectural trade-offs based on business needs, performance, cost, and long-term maintainability

o Contribute reusable patterns and documentation that support solution delivery across teams

o Stay informed on trends in cloud services, architecture frameworks, and GenAI tooling.

o Full Stack 5 years - Java / Python, CI / C pipelines must

o At least 2 years should be with Gen AI tools and framework.

o AWS - Must*

Requirements :

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 (, 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 (, LLMs, vector databases, prompt orchestration, LangChain, Bedrock)

Familiarity with AWS AI / ML services (, SageMaker, Bedrock, Comprehend, Lex)

AWS AI certification

Financial Services experience