Data Software Engineer-AI

7 -10 years

• More on DevOps, and AI Ops (used when Agentic AI comes into picture)

Platform & Framework Development

• Build reusable agentic AI frameworks, orchestration templates, and accelerators

• Develop shared libraries for:

• Tool orchestration

• Agent communication

• Memory handling

• Workflow management

• Evaluation pipelines

• Create standardized development patterns for enterprise AI systems

MCP & Integration Enablement

• Develop and maintain MCP-compatible integrations and enterprise connectors
• Build reusable APIs and integration services for enterprise platforms
• Enable scalable access to enterprise data sources and business tools

Governance & TRiSM Enablement

• Define lightweight governance standards for agentic AI systems
• Implement traceability, monitoring, logging, and lifecycle tracking mechanisms
• Support trust, risk, security, and monitoring (TRiSM) compliance
• Establish evaluation, observability, and auditability practices for AI agents

Engineering Enablement

• Create reusable templates, starter kits, and deployment accelerators
• Improve developer productivity through standardized tooling and automation
• Establish documentation standards and reusable implementation guides

Operational Excellence

• Support production readiness for AI systems
• Define monitoring, telemetry, guardrails, and fallback strategies
• Collaborate with solution teams to improve reliability and maintainability

Required Skills

Technical Skills

• Strong software architecture and platform engineering experience

• Expertise in:

• LangGraph / Semantic Kernel / AutoGen / CrewAI

• Orchestration frameworks

• AI system architecture

• MCP ecosystem concepts

• Strong backend engineering experience using Python/Node.js

• Experience building reusable platforms/frameworks

• Strong understanding of:

• AI governance

• Security

• Observability

• Evaluation frameworks

• Monitoring systems

• Experience with APIs, event-driven architectures, and cloud-native systems

Good to have Skills

• Experience with enterprise governance frameworks
• Familiarity with AI risk management and compliance practices
• Experience with DevSecOps and platform engineering
• Knowledge of vector databases, RAG systems, and enterprise search architectures