TalentBurst, an Inc 5000 company
Senior Full Stack GenAI Engineer
Base pay range: $95.00/hr - $106.61/hr
Duration: 6 months to start with, 6‑12 month contract with possibility of extension/conversion.
This hybrid position (3 days in office Tue‑Thu) is for local candidates only.
Responsibilities
Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval‑augmented generation (RAG).
Fine‑tune foundation models with 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 such as quantization, distillation, and caching to improve efficiency.
Drive experimentation with new models, agents, and frameworks (e.g., LangChain, LlamaIndex, OpenAI, Anthropic).
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.
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.
Requirements
10+ years of software engineering and development experience.
Proven experience building and deploying GenAI applications in production.
Strong programming skills in Python/JAVA and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face).
Deep understanding of LLMs, embeddings, and 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.
At least 2 years with GenAI tools and frameworks.
AWS certification (preferred).
Qualifications (Must Haves)
5‑6 years of full stack experience (Java/Python, CI/CD pipelines).
3+ years of GenAI framework and tool experience.
AWS - Must.
Exposure to GenAI tools (LangChain, Bedrock) and AWS AI/ML services (SageMaker, Comprehend, Lex).
Seniority level: Mid‑Senior level
Employment type: Contract
Job function: Information Technology
Industries: Staffing and Recruiting
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Duration: 6 months to start with, 6‑12 month contract with possibility of extension/conversion.
This hybrid position (3 days in office Tue‑Thu) is for local candidates only.
Responsibilities
Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval‑augmented generation (RAG).
Fine‑tune foundation models with 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 such as quantization, distillation, and caching to improve efficiency.
Drive experimentation with new models, agents, and frameworks (e.g., LangChain, LlamaIndex, OpenAI, Anthropic).
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.
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.
Requirements
10+ years of software engineering and development experience.
Proven experience building and deploying GenAI applications in production.
Strong programming skills in Python/JAVA and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face).
Deep understanding of LLMs, embeddings, and 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.
At least 2 years with GenAI tools and frameworks.
AWS certification (preferred).
Qualifications (Must Haves)
5‑6 years of full stack experience (Java/Python, CI/CD pipelines).
3+ years of GenAI framework and tool experience.
AWS - Must.
Exposure to GenAI tools (LangChain, Bedrock) and AWS AI/ML services (SageMaker, Comprehend, Lex).
Seniority level: Mid‑Senior level
Employment type: Contract
Job function: Information Technology
Industries: Staffing and Recruiting
#J-18808-Ljbffr