About the Role
We are seeking a talented engineer to drive the design, deployment, and continuous improvement of agentic AI applications . You will own the full lifecycle of agent frameworks, including toolchain architecture, prompt engineering, data integration, and observability, ensuring production-grade AI agents.
This role requires a visionary leader who combines deep technical expertise with business understanding, capable of designing end-to-end solutions, recommending the right infrastructure, and building strong engineering teams.
You will be responsible for rapid Proof of Concept (PoC) creation, guiding the transition to
production-grade systems , and ensuring timely, high-quality delivery.
Key Responsibilities
- AI & Agentic System Architecture
- Architect Agentic AI systems , including LLM orchestration, workflows, RAG pipelines, and automation.
- Evaluate and adopt modern AI frameworks, ensuring scalability and performance.
- LoB Application Architecture
- Independently architect enterprise-grade applications aligned with business needs.
- Translate business workflows into scalable, secure, and maintainable technical solutions.
- Infrastructure Strategy (AI + GenAI Focus)
- Assess and recommend infrastructure requirements specific to AI / GenAI applications , including :
- Vector databases, caching, and data pipelines for RAG workloads.
- Scalable storage and high-throughput networking for large model handling.
- Containerization (Docker, Kubernetes) for AI service orchestration.
- Cloud-native AI services (AWS Bedrock, Azure OpenAI, GCP Vertex AI) when suitable.
- Engineering Excellence
- Establish and enforce core engineering practices (CI / CD, testing, code reviews, documentation).
- Collaborate across teams to ensure alignment of technical design with business strategy.
Requirements
10+ years of experience in software engineering, with 5 + years in architecture roles .Strong background in AI / ML systems and enterprise software architecture .Hands-on expertise in :Experience with LLM orchestration tools (LangChain, LlamaIndex, AutoGen, etc.).Experience with observability & evaluation platforms (Langfuse, LangSmith).Familiarity with containerization (Docker, Kubernetes) and serverless computing.Strong Python coding skills and experience with REST / gRPC API integrations.Why Join Us?
Lead architecture for both AI-driven systems and LoB applications .Work on cutting-edge AI adoption while ensuring strong enterprise system design.Build and mentor your own team, shaping the future of enterprise transformation.Own the full cycle from PoC → enterprise-grade delivery across multiple domains.Key Skills – AI Application Architect
AI / ML solution architectureAgentic AI concepts and implementationsLangChain or similar LLM application frameworksPython, .NET Core / C#Azure (incl. Azure AI, Azure ML, ADF, Functions, Databricks)API design & integration (REST)MLOps practices & tools (MLflow, Azure ML)Containerization (Docker, Kubernetes) and Microservices architectureCI / CD with Azure DevOpsData engineering fundamentals (ETL / ELT)Architecture design (scalability, performance, security)