- Work hands-on with Product, Architecture, Engineering, QA, and UX teams to operationalize AI-DLC practices.

- Enable Mob Construction, AI-assisted development, prompt engineering, and context-driven delivery.

- Establish reference architectures, AI coding standards, reusable prompts, and semantic knowledge assets.

- Coach teams on validation frameworks, AI quality practices, and human-in-the-loop controls.

- Support brownfield semantic modeling and legacy system knowledge extraction.

- Introduce AI engineering toolchains, evaluation pipelines, and MLOps/LLMOps practices.

- Capture delivery learnings and convert them into reusable best practices.

Qualifications

- Bachelor's degree in Computer Science, Engineering, or related field

- 8+ years of software engineering, architecture, QA, DevOps, or platform engineering experience

- Hands-on experience delivering cloud-native and enterprise applications





- Experience with AI-assisted development tools and modern software engineering practices

- Robust coding and solution architecture background

- Preferred: Experience with LLMs, Agentic AI, RAG, semantic search, or AI platform

- Preferred: AWS/Azure/GCP certifications

- Preferred: Experience in AI platform engineering and MLOps/LLMOps

- Preferred: Financial Services domain experience

Technical & Soft Skills

- Prompt engineering and context engineering

- Python, Java, JavaScript, or modern cloud development stack

- DevOps, CI/CD, GitHub, GitHub Copilot, Cursor, Replit, etc.

- GenAI platforms and LLM integration, MLOps / LLMOps

- Semantic modeling and knowledge graph concepts

- Coaching and mentoring experience

- Collaboration across cross-functional teams

- Strong verbal and written communication

📌 Forward Deployed Engineer (FDE) (Chennai)
🏢 Orcapod Consulting Services
📍 Chennai