: Solution Architect (AI/Enterprise Systems)

Location: Mumbai, India Experience Required: 6+ Years Employment Type: Full-Time

About the Role

We are looking for an experienced Solution Architect to design and lead the implementation of scalable, enterprise-grade systems with a strong focus on AI agent workflows and LLM-based solutions. The ideal candidate will bridge business requirements with robust technical architecture, driving innovation across our AI and backend engineering initiatives.

Key Responsibilities

Design and architect end-to-end enterprise solutions, ensuring scalability, security, and performance.

Lead the design and development of AI agent workflows leveraging LLMs (Large Language Models) for automation and intelligent decision-making.

Define technical architecture, integration patterns, and best practices across microservices and API-driven systems.

Architect and oversee backend systems built on Python and FastAPI.

Evaluate, select, and implement AI agent frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or similar) suited to business use cases.

Collaborate with cross-functional teams (engineering, product, data science) to translate business requirements into technical solutions.

Establish architecture governance, coding standards, and design guidelines across projects.

Conduct technical feasibility studies, proof-of-concepts (POCs), and architecture reviews.

Ensure solutions align with enterprise architecture principles (scalability, reliability, security, and maintainability).





Mentor development teams on AI/LLM integration patterns and best practices.

Stay current with emerging trends in AI, LLM orchestration, and enterprise architecture.

Required Skills & Experience

6+ years of overall experience in software engineering/architecture roles.

Proven experience in Enterprise Architecture — designing large-scale, distributed, and scalable systems.

Hands-on experience building AI agent / LLM-based workflows (multi-agent systems, orchestration, RAG pipelines, tool-calling, etc.).

Strong proficiency in Python for backend and AI system development.

Solid experience building APIs using FastAPI.

Practical experience with AI agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.

Strong understanding of microservices architecture, cloud platforms (AWS/Azure/GCP), and containerization (Docker/Kubernetes).

Experience with vector databases and embeddings (e.g., Pinecone, Weaviate, FAISS, Chroma) is a plus.

Good understanding of system design principles, integration patterns, and API security.

Excellent problem-solving, communication, and stakeholder management skills.

Positive to Have

Experience with cloud-native AI services (Azure OpenAI, AWS Bedrock, Vertex AI).

Exposure to MLOps/LLMOps practices for deploying and monitoring AI systems.

Prior experience in a client-facing or presales architecture role.

Relevant certifications (Solution Architect, Cloud Architect, or AI/ML certifications).

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