AI Application Architect

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 architecture

Agentic AI concepts and implementations

LangChain or similar LLM application frameworks

Python, .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 architecture

CI / CD with Azure DevOps

Data engineering fundamentals (ETL / ELT)

Architecture design (scalability, performance, security)