• Role: Gen AI Engineer • Location: Remote (US) • Number of roles: 3 • Type: Fulltime or Contract Job Description Solution Engineering & Delivery • Translate business requirements into robust, scalable AI solutions using RAG, embeddings, vector search, and fine-tuning. • Design, prototype, and implement LLM-driven applications with multi-step agent workflows and orchestration frameworks (e.g., LangGraph, LangChain, LlamaIndex). • Build and maintain APIs, services, and reusable components in Python to support AI applications. • Deploy and monitor AI models in cloud-native environments (GCP, Azure) leveraging Kubernetes, serverless, and MLOps pipelines. • Continuously evaluate model/system performance and implement improvements. Architecture & Standards • Contribute to the design of modular and reusable AI architectures across projects. • Establish and follow engineering best practices for GenAI development, testing, deployment, and monitoring. • Support the creation of documentation, templates, and playbooks for consistent solution delivery. Collaboration & Integration • Partner with cross-functional teams to integrate AI capabilities into enterprise applications. • Work closely with business stakeholders to translate challenges into AI-powered solutions. • Share lessons learned and help drive adoption of AI practices across teams. • Ensure AI applications align with security, compliance, and responsible AI standards. Minimum Requirements • Bachelors or Masters degree in Computer Science, AI/ML, or related technical field. • 5+ years of software development experience, with strong proficiency in Python. • 3 - 5+ years hands-on experience building GenAI/LLM-based applications, with proven success from PoC to production deployment. • Proficiency in designing retrieval pipelines (document loaders, chunking strategies, embeddings, vector databases like FAISS, Pinecone, ChromaDB). • Expertise in LLM APIs (OpenAI, Claude, Gemini, etc.), prompt engineering, and fine-tuning. • Experience with cloud platforms (GCP, Azure), containerization (Docker, Kubernetes), and MLOps (CI/CD, monitoring). • Strong understanding of API design, microservices, and enterprise integration patterns. • Familiarity with version control systems (e.g., Git, Azure DevOps). • Demonstrated ability to build and scale AI solutions in production. Preferred Qualifications • Experience with orchestration frameworks (LangGraph, LangChain, LlamaIndex). • Familiarity with DevOps practices such as IaC (Terraform), YAML pipelines, and automation. • Strong communication skills with ability to collaborate across teams and articulate technical concepts clearly. • Proactive, self-motivated problem solver with a track record of delivering high-value solutions. • Leverage vibe and agentic coding tools such as Cursor, Claude Code, and similar frameworks to accelerate AI solution development and orchestrate multi-agent workflows. Additional Attributes • Analytical mindset with focus on measurable outcomes. • Collaborative team player who thrives in cross-functional environments. • Curiosity and drive to stay current with emerging GenAI technologies.