Gen AI Engineer

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.