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Artificial Intelligence Engineer

Artificial Intelligence Engineer

TekIT Software Solutions Pvt. Ltd.Pune
3 days ago
Job description

Position : AI Engineer.

Key Responsibilities :

  • 4- 6 years of hands-on expertise in AI / ML, Generative AI, and Agentic AI systems for Pune location.
  • Design, build, and deploy AI / ML models for classification, prediction, recommendation, and optimization.
  • Build and deploy REST APIs for ML / AI models using frameworks such as Flask or FastAPI.
  • Apply asynchronous programming and high-performance API design.
  • Work with Generative AI frameworks (LLMs, Diffusion models, Transformers, etc.) to develop next-gen AI solutions.
  • Build and orchestrate Agentic AI systems capable of reasoning, planning, and executing tasks autonomously.
  • Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases.
  • Manage model versioning, monitoring, and scaling for APIs in production environments.
  • Implement API authentication and security (JWT, OAuth, etc.)
  • Integrate AI models with APIs, databases, and enterprise systems for end-to-end workflows.
  • Evaluate model performance, scalability, and reliability, ensuring alignment with business goals.
  • Research, prototype, and productionize cutting-edge AI techniques.
  • Collaborate with product managers, data scientists, and engineers to deliver scalable AI-driven applications.

Required Skills & Experience :

  • 4- 6 years of hands-on experience in AI / ML engineering.
  • Strong coding skills in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
  • Expertise in Generative AI (LLMs like GPT, LLaMA, Claude, diffusion models, etc.)
  • Experience with Agentic AI frameworks (LangChain, LlamaIndex, AutoGPT, CrewAI, or similar).
  • Solid understanding of NLP, embeddings, and vector databases (Pinecone, Weaviate, FAISS, Milvus).
  • Strong knowledge of the ML lifecycle (data preprocessing, training, evaluation, deployment).
  • Expertise in building REST APIs with FastAPI / Flask and integrating them into applications.
  • Experience with containerized solutions using Docker & Kubernetes.
  • Deployment experience across APIs, containers, and cloud platforms (AWS / GCP / Azure).
  • Proficiency in prompt engineering, RAG (Retrieval Augmented Generation), and model fine-tuning.
  • Strong problem-solving, debugging, and optimization skills.

    • (ref : hirist.tech)

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