Enterprise Generative AI Engineers (Lead Mid-Level)
Location: Remote
Engagement Type: Contract (Offshore/Nearshore)
Team Size: 23 (1 Lead + 12 Engineers)
Duration: Flexible based on project scope
About The Role
We are seeking a small, high-impact team of
Enterprise Generative AI Engineers to design, build, and deploy production-grade AI solutions across multiple industry verticals. This role is ideal for professionals experienced in delivering end-to-end AI systems from prototyping to scalable deployment.
The Team Will Include
- A Senior Lead responsible for architecture, technical direction, and stakeholder engagement
- Mid-Level Engineers focused on hands-on development and implementation
You will work in a fast-paced, cross-functional environment, collaborating with business stakeholders, product teams, and engineering groups to deliver scalable AI solutions.
Key Responsibilities
AI Solution Development - Design and implement LLM-powered applications such as:
- Retrieval-Augmented Generation (RAG) pipelines
- AI agents and multi-agent systems
- Chatbots and generative AI integrations
- Integrate with commercial and open-source LLMs (OpenAI, Anthropic, Llama, Mistral)
ML Engineering Pipelines - Build and optimize ML/data pipelines for:
- Training, fine-tuning, and evaluation
- Embeddings and vector search workflows
- Develop scalable and reusable AI/ML components
Infrastructure MLOps - Architect and manage production-grade AI infrastructure
- Implement:
- Containerization (Docker, Kubernetes)
- CI/CD pipelines for ML workflows
- Model monitoring, logging, and scaling strategies
Stakeholder Collaboration - Engage with business stakeholders to:
- Understand requirements
- Identify AI use cases
- Translate ambiguous needs into technical solutions
- Collaborate with cross-functional teams to align AI solutions with business goals
Best Practices Documentation - Establish standards for:
- Prompt engineering
- Model evaluation
- Responsible AI practices
- Document system architecture, workflows, and operational runbooks
Required Qualifications
Senior Lead (7+ Years Experience) - Proven experience delivering enterprise-scale AI/ML systems in production
- Strong expertise in:
- Python, PyTorch/TensorFlow
- Modern ML/AI frameworks and ecosystems
- Hands-on experience with cloud platforms (AWS, GCP, or Azure)
- Deep knowledge of:
- Kubernetes, Docker, and container orchestration
- MLOps and scalable ML infrastructure
- Expertise in LLM application patterns :
- RAG, embeddings, vector databases, function calling
- Strong leadership and communication skills:
- Ability to lead architecture decisions
- Mentor engineers
- Drive stakeholder discussions and discovery sessions
Mid-Level Engineers (37 Years Experience) - Hands-on experience building ML models and data pipelines
- Proficiency in:
- Python
- At least one deep learning framework (PyTorch preferred)
- Working knowledge of:
- Cloud platforms (AWS/GCP/Azure)
- Docker and Kubernetes
- Familiarity with:
- LLM APIs and prompt engineering
- RAG and vector database concepts
- Ability to:
- Work independently
- Translate requirements into high-quality implementations
Nice to Have - Experience with MLOps tools (MLflow, Weights Biases, SageMaker, Vertex AI)
- Background in:
- NLP, computer vision, or time-series forecasting
- Experience with:
- Multi-agent AI systems or orchestration frameworks
- Vector databases (Pinecone, Weaviate, pgvector)
- Contributions to open-source AI/ML projects
- Familiarity with geospatial or remote sensing data
Core Tech Stack
- Languages Python (primary), JavaScript/TypeScript
- ML/AI PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex
- LLM APIs OpenAI, Anthropic, Llama, Mistral
- Cloud AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (OpenAI Service)
- Infrastructure Docker, Kubernetes, Terraform, CI/CD
- Data PostgreSQL, Redis, Vector DBs (Pinecone, Weaviate, pgvector)
Why Join
- Work on cutting-edge Generative AI and LLM applications
- Build end-to-end production AI systems
- Collaborate with experienced professionals in a high-impact, fast-paced environment
- Flexible, fully remote engagement
This job is provided by Shine.com
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