AI Engineer
- Exponentia.ai
- 3 - 5 years
- Mumbai
- 11 hours ago
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Job Description
Role Overview
We are seeking a highly skilled AI Engineer with hands-on experience in AI/ML, Generative AI, and Agentic AI systems. The ideal candidate will have a deep understanding of AI agent frameworks, Model Context Protocol (MCP), Databricks, and cloud-native MLOps workflows. This role involves building, deploying, and optimizing intelligent systems from LLM-powered applications to autonomous multi-agent architectures.
Core Responsibilities
- Design, develop, and deploy machine learning and generative AI models in production environments.
- Build and integrate agentic AI systems intelligent agents capable of reasoning, planning, and multi-step decision-making.
- Develop and maintain data pipelines and MLOps workflows using Databricks, MLflow, and cloud-native tools.
- Integrate LLMs and AI agents with external APIs, databases, and tools using agent frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel, LangGraph).
- Implement and manage Model Context Protocol (MCP) connections between agents and enterprise systems.
- Optimize AI workloads in AWS, Azure, or GCP environments with scalable, secure infrastructure.
- Collaborate with cross-functional teams (data, cloud, and product) to deliver AI-driven solutions.
- Ensure AI system security, observability, explainability, and compliance with governance standards
Roles and Responsibilities
Key Technical Skills
AI / ML & Data Science
- Strong foundation in machine learning, deep learning, and data science concepts.
- Expertise in Python with ML libraries: PyTorch, TensorFlow, scikit-learn, pandas, NumPy.
- Knowledge of model evaluation, feature engineering, and transfer learning.
- Experience with vector databases (FAISS, Pinecone, ChromaDB).
Generative AI & NLP
- Hands-on experience with LLMs, prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning.
- Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
- Implementation of text generation, summarization, classification, and document Q&A systems.
Agentic AI, Agent Frameworks & MCP
- Deep understanding of agentic AI systems autonomous, multi-step, tool-using architectures.
- Practical experience building AI agents using frameworks such as LangChain, AutoGen, CrewAI, LangGraph, or Semantic Kernel.
- Experience designing multi-agent collaboration systems and task orchestration.
- Hands-on experience implementing or integrating Model Context Protocol (MCP) for tool invocation, context sharing, and agent-to-system communication.
- Strong awareness of safety, governance, auditability, and agent evaluation frameworks.
Databricks, MLOps & Data Engineering
- Strong experience with Databricks (Spark, Delta Lake, MLflow, feature store).
- End-to-end experience in data pipelines, ETL/ELT processes, and real-time streaming.
- Proficiency in MLOps best practices: model registry, versioning, drift detection, rollback.
- Observability and automation for deployed ML systems.
Cloud & Infrastructure
- Hands-on with AWS / Azure / GCP for AI workloads.
- Familiarity with SageMaker, Azure ML, or Vertex AI.
- Experience with Docker, Kubernetes, and serverless deployments.
- Working knowledge of Infrastructure as Code (Terraform / CloudFormation) and CI/CD pipelines.
Software Engineering & APIs
- Strong programming and software design fundamentals.
- Experience building REST / GraphQL APIs and microservices.
- Event-driven and asynchronous architectures (Kafka, Pub/Sub, message queues).
- Integration of AI components with enterprise software systems.
Security, Observability & Responsible AI
- Knowledge of monitoring, logging, and tracing (Prometheus, Grafana, OpenTelemetry).
- Implementation of secure AI practices access control, secrets management, prompt injection defense.
- Understanding of model explainability, bias mitigation, and ethical AI considerations.
Preferred / Nice-to-Have Skills
- Familiarity with reinforcement learning and planning-based agents.
- Experience with knowledge graphs and symbolic reasoning.
- Building multi-modal agents (text + vision + audio).
- Contributions to open-source AI / agent frameworks.
- Exposure to edge or on-device AI systems.
Soft Skills
- Strong analytical and problem-solving skills.
- Excellent communication and documentation abilities.
- Ability to work cross-functionally in fast-paced, research-driven environments.
- Curious mindset with a passion for emerging AI technologie
Job Classification
Industry: Emerging TechnologiesFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: Exponentia.aiLocation(s): Mumbai
Keyskills: fundamentals analytical software design tools sql cloud gen deep learning data science safety programming ml communication skills python natural language processing documentation microsoft azure engineering machine learning stp data bricks system framework aws governance
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