Experience- 12+Years
Key Responsibilities
- Design end-to-end multi-agent architectures, including:
- Agent orchestration
- Inter-agent communication
- Memory management
- Tool/function calling
- Human-in-the-loop workflows
- Build foundational AI agents and reusable frameworks/templates.
- Set engineering standards through code contributions, pull request reviews, and architecture guidance.
- Architect secure integrations with enterprise platforms such as:
- Salesforce
- SAP
- Microsoft Dynamics
- ServiceNow
- Other business applications using APIs, events, and MCP-based tool servers.
- Design scalable, secure, and highly available AI systems with focus on:
- Multi-tenancy
- LLM Guardrails
- Prompt Injection Protection
- PII Handling
- Observability
- Agent Evaluation
- Ensure compliance with data privacy, residency, and enterprise security requirements.
- Lead and mentor a team of AI engineers by defining:
- Coding standards
- Design patterns
- Release governance
- Best engineering practices
- Present technical solutions to CXOs and enterprise IT stakeholders.
- Translate business challenges into scalable Agentic AI solutions.
- Collaborate with delivery leadership on:
- Solution estimation
- Project planning
- Technical risk management
Required Qualifications
- 12+ years of hands-on software engineering experience with a strong technical career progression, including Architect-level responsibilities.
- Proven experience architecting and delivering at least one enterprise-grade multi-agent AI system in production (not just a proof of concept).
- Minimum 3+ years of experience building LLM/Generative AI applications, including:
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Structured Outputs
- Tool Calling across multiple LLM providers
- Hands-on experience with at least one major Agent Framework:
- LangGraph
- CrewAI
- AutoGen
- OpenAI Agents SDK
- Amazon Bedrock Agents / Strands
- Microsoft Semantic Kernel
- Strong understanding of:
- Multi-agent orchestration
- Agent-to-agent communication
- Memory and state management
- Experience implementing Model Context Protocol (MCP) and tool-use architectures, including permissioning and sandboxing.
- Strong programming skills in Python (TypeScript/Node.js is a plus).
- Experience with:
- Production-grade testing
- CI/CD
- API development
- Cloud-native architecture experience on AWS and/or Azure, including:
- Containers
- Serverless Computing
- Event-driven Architectures
- Infrastructure as Code (IaC)
- Vector Databases
- Deep understanding of enterprise architecture principles covering:
- Scalability
- Availability
- Security
- Vulnerability Management
- OWASP Top 10
- OWASP LLM Top 10
- Zero Trust Security
- Disaster Recovery (DR)
- Business Continuity Planning (BCP)
- Experience integrating enterprise applications such as:
- Salesforce
- Microsoft Dynamics
- ServiceNow
- SAP
Preferred Qualifications
- Experience working with clients in the Middle East, especially government or semi-government organizations.
- Experience building multilingual conversational AI systems (Arabic/English preferred).
- Certifications such as:
- AWS Solutions Architect – Professional
- AWS Machine Learning Specialty
- Azure Solutions Architect Expert
- Experience with:
- Model Fine-tuning
- Model Distillation
- Self-hosted/Open-weight LLM deployment
- Contributions to the AI community through:
- Open-source projects
- Technical blogs
- Conference speaking
- Research publications
Pay: ₹1,000,000.00 - ₹2,400,000.00 per year
Work Location: In person
