Senior GenAI Engineer (Hybrid) :: W2 Role Only
DMS Vision Inc
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Please find the job description given below and let me know your interest.
Position: Senior GenAI Engineer (Hybrid)
Location: Atlanta / Bay Area / Charlotte / Chicago / Cincinnati / Dallas-Metro / Denver / Milwaukee / MSP / NY / Portland / St. Louis
Duration : 6-12 months
Job Description:
Job Summary
The Senior Engineer (Generative AI) is responsible for designing, developing, and deploying scalable Generative AI (GenAI) solutions within an enterprise environment. This role requires strong hands-on expertise in LLM-based applications, GenAI architectures, and modern cloud-native engineering practices.
The position partners closely with cross-functional teams to build production-ready AI systems that meet enterprise standards for scalability, security, and reliability.
---
Key Responsibilities
1. GenAI Solution Development
Develop and implement GenAI applications leveraging:
o Large Language Models (LLMs)
o Retrieval-Augmented Generation (RAG) architectures
o Prompt engineering techniques
o Agentic AI concepts and workflows
Build intelligent pipelines using frameworks such as LangChain, LangGraph, and Microsoft Foundry Agent Service
Evaluate solution performance, accuracy, and scalability of GenAI implementations
2. GenAIOps & Lifecycle Support
Contribute to the end-to-end GenAI lifecycle, including:
o Solution design and development
o Integration and deployment
o Performance tuning and optimization
Support secure deployment, horizontal scaling, and operational stability of GenAI workloads
Assist in implementing monitoring, logging, and observability practices for production environments
3. Cloud, Platform & Scalability Engineering
Develop and deploy GenAI systems across cloud platforms (Azure and AWS)
Contribute to distributed system design for scalable AI workloads
Utilize modern infrastructure practices:
o Containerization (Docker)
o Orchestration (Kubernetes)
o Infrastructure as Code (Terraform, ARM/Bicep)
Ensure solutions meet enterprise expectations for availability, performance, and security
4. Software Engineering & Delivery Excellence
Develop scalable applications using Python and microservices-based architectures
Apply secure coding standards and proper data handling practices for enterprise, regulated environments
Contribute to CI/CD pipelines, automated testing, and deployment workflows
Participate in code reviews and adhere to engineering best practices
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Required Qualifications
Bachelor's degree in Computer Science, Engineering, or related field
5 8 years of experience in software engineering, AI/ML, or platform engineering
Hands-on experience with GenAI systems, including LLMs and RAG architectures
Understanding of agentic AI concepts and exposure to frameworks such as LangChain or LangGraph
Experience with cloud platforms (Azure and/or AWS)
Knowledge of distributed systems and scalable application design
Proficiency in Python development
Experience with Docker, Kubernetes, and Infrastructure as Code tools
---
Preferred Qualifications
Experience deploying GenAI or ML solutions in production environments
Familiarity with observability and monitoring tools
Understanding of AI governance, compliance, and security practices
Experience in financial services or other regulated industries
---
Core Competencies
Technical Execution
Applies strong software engineering fundamentals to build production-grade systems
Delivers reliable, scalable, and maintainable GenAI solutions
Systems Thinking
Understands distributed systems and cloud-native architectures
Designs for scalability, performance, and resiliency
Learning & Innovation
Keeps pace with evolving GenAI technologies and frameworks
Continuously improves solution quality through experimentation
Collaboration & Delivery
Works effectively across engineering and product teams
Delivers against commitments with strong ownership and accountability
If you are interested, please share your updated resume and suggest the best number & time to connect with you .
Ajit Kumar
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