AI/ML Solution Architect

Predikly Technologies; Pune District; Hybrid; INR 6,000,000 - 9,000,000; Full time

Job summary

Predikly Technologies seeks a Gen AI & ML Architect in Pune, hybrid mode, to own end-to-end design and delivery of production-grade AI solutions. You will lead a 5-10 person AI/ML team, write code, review models, and drive architectural decisions in a hands-on player-coach role.

Responsibilities span agentic AI systems, RAG pipelines, vector search, multi-provider LLMs, cloud infrastructure, and full-stack AI apps, with collaboration across product, delivery, and client stakeholders to align

Qualifications

• 8–10 years of total software/AI engineering experience.
• Minimum 3 years in hands-on Generative AI & ML project delivery in production.
• Proven experience leading a team of 5-10 AI/ML developers with direct delivery responsibility.
• Demonstrated track record shipping agentic AI systems to real customers.
• Experience working in an Agile/Scrum delivery model.

Responsibilities

• Lead a team of 5-10 Gen AI & ML Developers, driving accountability and technical excellence.
• Conduct code reviews, design reviews, and sprint ceremonies; set engineering standards.
• Collaborate with product managers, delivery leads, and client stakeholders to prioritise roadmaps.
• Design and build production-grade agentic AI systems for real customer use cases.
• Define agent memory, planning, reflection, and tool-call patterns.
• Architect and implement solutions using LangChain, LangGraph, AutoGen, CrewAI.
• Ensure production-readiness: latency SLAs, cost budgets, observability.
• Work hands-on with leading LLM providers and design RAG pipelines.

Skills

Team Leadership

Gen AI & ML expertise

Hands-on coding

Architectural design

Client stakeholder communication

Experimentation & rigour

Education

B.E. / B.Tech / M.Tech in Computer Science, AI/ML, Data Science, or a related technical discipline

Tools

LangChain

LangGraph

AutoGen

CrewAI

Pinecone

Weaviate

Qdrant

FAISS

AWS SageMaker

Azure ML

Vertex AI

GitHub Actions

Kubeflow

Job description

Predikly hiring for Gen AI & ML Architect.

Job Location : Shivajinagar, Pune

Mode : Hybrid

ROLE PURPOSE

As Gen AI & ML Architect, you will own the end-to-end design, development, and delivery of production-grade Gen AI and Machine Learning solutions for Predikly's clients. You will lead a team of 5-10 AI/ML engineers, drive technical architecture decisions, and serve as a hands‑on contributor writing code, reviewing models, and solving complex problems alongside your team. This is a player‑coach role demanding both individual technical depth and team leadership maturity.

KEY RESPONSIBILITIES

1. Team Leadership & Mentoring

• Lead, manage, and mentor a team of 5-10 Gen AI & ML Developers, driving accountability, growth, and technical excellence.
• Conduct code reviews, design reviews, and sprint ceremonies; set engineering standards and best practices.
• Collaborate with product managers, delivery leads, and client stakeholders to define roadmaps and prioritise backlogs.
• Foster a culture of experimentation, continuous learning, and engineering rigour within the AI/ML team.

2. Agentic AI Development

• Design and build production-grade agentic AI systems for real customer use cases — including multi-agent orchestration, autonomous reasoning pipelines, and tool‑use patterns. Architect and implement solutions using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, and custom agent orchestration layers.
• Define agent memory, planning, reflection, and tool‑call patterns aligned with real‑world reliability requirements.
• Ensure agents meet production‑readiness criteria: latency SLAs, cost budgets, fallback handling, and observability.

3. Gen AI & LLM Engineering

• Work hands‑on with leading LLM providers: OpenAI (GPT-4o, o1), Anthropic Claude, Google Gemini, and open‑source models (LLaMA, Mistral).
• Design and implement Retrieval‑Augmented Generation (RAG) pipelines with hybrid search, re‑ranking, and context compression.
• Engineer advanced prompting strategies: chain‑of‑thought, structured output, few‑shot, system persona, and dynamic routing.
• Build vector search & embedding pipelines using tools such as Pinecone, Weaviate, Qdrant, pgvector, and FAISS.
• Evaluate, fine‑tune, and benchmark models; manage prompt versioning and model drift monitoring.

4. Machine Learning Engineering

• Design and deliver end‑to‑end ML pipelines: data ingestion, feature engineering, model training, evaluation, and deployment.
• Apply ML techniques including classification, regression, clustering, NLP, time‑series forecasting, and transformer‑based architectures.
• Leverage MLflow, Weights & Biases, or Kubeflow for experiment tracking, model registry, and pipeline orchestration.
• Implement monitoring and feedback loops for model drift, data drift, and retraining triggers in production.

5. Cloud Architecture & Infrastructure

• Architect and deploy AI/ML workloads on AWS, Azure, and GCP using managed AI services and custom containerised deployments.
• Use AWS SageMaker, Azure ML, Google Vertex AI, Lambda, ECS, and serverless patterns to build scalable AI services.
• Design secure, cost‑optimised cloud architectures; apply IAM, VPC, secrets management, and cost tagging best practices.
• Set up CI/CD pipelines for ML workflows using GitHub Actions, Azure DevOps, or AWS CodePipeline.

6. Full‑Stack AI Application Development

• Contribute to and guide development of AI‑powered web applications using React, Angular, Next.js on the frontend and Node.js on the backend.
• Design and manage databases including PostgreSQL, MySQL (relational) and MongoDB, DynamoDB, Redis, Elasticsearch (NoSQL).
• Build REST and GraphQL APIs that surface AI capabilities to end‑user products; ensure API security, versioning, and documentation.
• Integrate AI/ML model outputs into product UIs with appropriate UX patterns for streaming, latency masking, and error handling.

7. Client Orientation & Stakeholder Engagement

• Serve as the primary technical interface for client engagements — leading discovery workshops, solution walkthroughs, and sprint demos to build confidence and trust with business and technical stakeholders.
• Translate complex AI/ML concepts, architectural trade‑offs, and model limitations into clear, business‑relevant language that non‑technical clients and product owners can act on. Collaborate with client teams to identify high‑impact AI use cases, define success metrics, and ensure delivered solutions align with stated business outcomes — not just technical specifications.

REQUIRED QUALIFICATIONS & EXPERIENCE

Experience

• 8–10 years of total software/AI engineering experience.
• Minimum 3 years in hands‑on Generative AI & ML project delivery in production environments.
• Proven experience leading a team of 5-10 AI/ML developers with direct responsibility for delivery, quality, and team development.
• Demonstrated track record of shipping agentic AI systems to real customers — not just PoCs or prototypes.
• Experience working in an Agile/Scrum delivery model, including sprint planning, stand‑ups, retrospectives, and stakeholder demos.\

Education

• B.E. / B.Tech / M.Tech in Computer Science, AI/ML, Data Science, or a related technical discipline.