Ai Ml Architect

Birch Tree Consulting; Dadri; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Birch Tree Consulting is seeking a senior solution architect to lead end-to-end AI/ML and Generative AI initiatives. You will design RAG systems, vector search, embedding pipelines, and AI agents while guiding multi-disciplinary teams through discovery, design, and delivery.

The role demands hands-on work with Snowflake Cortex, Snowpark ML, and cloud integrations (AWS/Azure/GCP), ensuring governance, security, and scalable architectures across client engagements.

Qualifications

• 10+ years of experience in solution architecture, AI/ML architecture, enterprise architecture, or technical delivery.
• Hands-on experience building production AI/ML and Generative AI solutions.
• Experience with LLMs, RAG, vector databases, embedding pipelines, agentic AI, prompt engineering, and AI evaluation.
• Strong knowledge of ML, DL, NLP, MLOps, and LLMOps.
• Hands-on with Snowflake Cortex tools and Snowflake cloud integrations.

Responsibilities

• Architect and deliver end-to-end AI/ML solutions from discovery to deployment.
• Design production-grade RAG, vector search, embedding pipelines, AI agents, copilots, and multi-agent workflows.
• Lead hands-on implementations using Snowflake Cortex and related tools.
• Design scalable ML/LLM pipelines for training, inference, evaluation, monitoring, governance.
• Integrate AI solutions with AWS, Azure, or GCP and enterprise systems.

Skills

Solution Architecture

AI/ML Architecture

LLMs/RAG

Snowflake Cortex

Cloud Platforms

MLOps

Governance

Stakeholder Management

Pre-Sales

Technical Leadership

Tools

Snowflake Cortex

Cortex Analyst

Cortex Search

Cortex Agents

Snowpark ML

Snowflake Native Apps

Kafka

Job description

Key Responsibilities :

• Architect and deliver end-to-end AI/ML and Generative AI solutions from discovery through production deployment.
• Design production-grade RAG systems, vector search solutions, embedding pipelines, AI agents, copilots, and multi-agent workflows.
• Lead hands-on implementation using Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and related Snowflake AI capabilities.
• Design scalable ML and LLM pipelines supporting training, inference, evaluation, monitoring, and governance.
• Integrate AI solutions with AWS, Azure, or GCP, as well as enterprise applications, APIs, ETL/ELT platforms, streaming systems, and third-party AI services.
• Define reusable AI reference architectures, accelerators, technical standards, and governance frameworks.
• Provide technical leadership through architecture reviews, code reviews, design sessions, and production-readiness assessments.
• Lead client discovery workshops, solution design, effort estimation, technical presentations, proof-of-concepts, and pre-sales activities.
• Collaborate with data engineers, ML engineers, application teams, architects, and business stakeholders throughout delivery.

Required Qualifications

• 10+ years of experience in solution architecture, AI/ML architecture, enterprise architecture, or technical delivery.
• Strong recent hands-on experience building and supporting production AI/ML and Generative AI solutions.
• Proven experience with LLMs, RAG, vector databases, embedding pipelines, agentic AI, prompt engineering, and AI evaluation.
• Strong understanding of machine learning, deep learning, NLP, MLOps, and LLMOps.
• Hands-on experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps.
• Strong architecture experience across Snowflake and at least one major cloud platform, preferably AWS or Azure.
• Experience integrating AI platforms with APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures.
• Strong understanding of AI security, governance, compliance, observability, and model monitoring.
• Excellent client-facing communication, technical leadership, and stakeholder-management skills.
• Ability to balance strategic architecture ownership with hands-on technical execution.

Preferred Qualifications :

• Experience with Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Azure ML, or Vertex AI.
• Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or MCP.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, or pgvector.
• Experience integrating AI solutions with platforms such as Salesforce, ServiceNow, SAP, Workday, or Microsoft applications.
• Snowflake, AWS, Azure, or AI/ML certifications.
• Consulting experience within regulated industries such as financial services, healthcare, or manufacturing.