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 up-to-date 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
Robust verbal and written communication

📌 Forward Deployed Engineer Fde Chennai
🏢 Orcapod Consulting Services
📍 Chennai