Artificial Intelligence Consultant

Role Summary :

We are seeking an experienced AI / ML Consultant with deep expertise in Agentic AI development and the Google AI ecosystem. In this role, you will design and deliver end-to-end AI solutions, leveraging modern frameworks to build high-impact, production-grade AI systems.

This is a full-time, permanent position based in Pune, India, with a hybrid work model (three days in office). As part of our AI Solutions and Delivery team, you will play a key role in shaping real-world AI adoption across our projects.

We are looking for candidates with strong hands-on experience in AI / ML development within the Google AI ecosystem. The ideal candidate will also have experience with workflow automation tools such as n8n or Zapier, and integration platforms like MuleSoft, Boomi, or similar. Strong Python development skills are essential, along with experience on at least one major cloud platform (AWS, Azure, or GCP) and solid MLOps knowledge—including CI / CD for ML, model deployment, and monitoring.

Roles & Responsibility :

Build intelligent agent workflows using frameworks such as LangChain, Llama Index, Haystack, and related technologies.

Design and implement RAG pipelines and integrate vector databases to support knowledge-intensive applications.

Work extensively with Vertex AI, Gemini APIs, Agent Builder / Agentic Frameworks, and Agent Garden / ADK to develop scalable AI solutions.

Leverage tools such as BigQuery ML, Cloud Run, and Pub / Sub to architect and deploy cloud-native AI workflows.

Build automation workflows using n8n or Zapier, and integrate enterprise systems via platforms like MuleSoft, Boomi, or similar.

Design and implement AI solutions using strong Python development skills across AWS, Azure, or GCP environments.

Set up and manage MLOps practices including CI / CD for ML, model deployment, monitoring, and performance optimization.

Lead AI use cases from discovery and PoC stages through to full production deployment, collaborating with cross-functional teams to ensure successful delivery and user adoption.

Required skills :

2–3 years of hands-on experience working with agentic AI frameworks such as LangChain, Llama Index, Haystack, or similar.

Strong understanding of tools and services within the Google stack, including Vertex AI, Gemini APIs, Agent Builder / Agentic Frameworks, Agent Garden / ADK, BigQuery ML, Cloud Run, Pub / Sub, RAG pipelines, vector databases, and LLM fine-tuning.

Familiarity with workflow automation tools like n8n or Zapier, and integration platforms such as MuleSoft, Boomi, or equivalent.

Proficiency in Python along with experience on at least one major cloud platform (AWS, Azure, or GCP).

Solid grasps of MLOps concepts and tools, including CI / CD for ML, model deployment, monitoring, and performance oversight.

Demonstrated ability to take AI solutions from ideation and development through to deployment and production use.

Exposure to multi-cloud or hybrid architectures, along with working knowledge of prompt engineering and LLM fine-tuning methods.

Nice to have :

Google Cloud ML / Architect, NVIDIA AI, or Microsoft AI Engineer certifications.

Familiarity with Hugging Face, vLLM, Ray Serve, or FastAPI for scalable AI deployments.

Exposure to multi-agent systems, LLM evaluation tools, and basic AI safety / guardrail practices.

Familiarity with Docker, Kubernetes, and workflow tools like Vertex AI Pipelines or Kubeflow.

Experience with ETL / ELT pipelines or streaming tools like Airflow, dbt, or Kafka.