Director of Software Engineering - Python, Gen AI
INR 4000K-6000K (estimate) Executive-level Full Time
Tasks
- Add guardrails for LLM systems
- Apply prompt engineering strategies
- Build and ship AI solutions end to end
- Build reusable tooling and infrastructure
- Collaborate with AI ML legal compliance privacy cybersecurity and model risk teams
- Contribute evaluation harnesses and prompt libraries
- Contribute to team best practices for AI augmented engineering
- Create evaluation frameworks
- Design develop test and deploy AI powered applications
- Develop agentic workflows
- Establish validation security resiliency traceability and reuse guardrails
- Implement retrieval-augmented generation pipelines
- Improve SDLC and TLM automation
- Lead test modernization automation and incident triage acceleration
- Maintain model risk artifacts and validation evidence
- Maintain system design documentation
- Monitor drift performance cost fairness
- Present results to technical and non-technical audiences
- Set direction and governance for agentic AI enabled engineering
- Support MLOps and LLMOps practices
- Support incident response
- Use AI-assisted development tools
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | Anthropic | B testing | Bias/fairness | CI/CD | Causal Inference | Code review | Cost Optimization | Distributed Systems | Docker | Drift Detection | Embeddings | Evaluation Frameworks | Git | Governance | Hallucination mitigation | Hugging Face | Human-in-the-loop | Infrastructure as Code | LLM APIs | LLMOps | MLOps | Machine Learning | Model Risk Management | Model risk | Monitoring | OpenAI | Performance optimization | Prompt engineering | PyTorch | Python | RAG | REST APIs | Red Teaming | Red team | Red team exercises | Resiliency | Responsible AI | Retrieval-Augmented Generation | Risk Management | Security | Software Engineering | Spark | Team exercises | TensorFlow | Testing | The Loop | Tokenization | Traceability | Validation | Vector Databases | “as-code”
Education
N/A
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