Data Science

13 hours ago

Vizag, Andhra Pradesh, India Space Inventive Full time

Job Description:-

We are seeking a visionary Data Science/AI ML Architect to lead the design and integration of cutting-edge AI systems, including Generative AI, Large Language Models (LLMs), multi agent orchestration, and retrieval-augmented generation (RAG) frameworks. This role demands a strong technical foundation in machine learning, deep learning, and AI infrastructure, along with hands-on experience in building scalable, production-grade AI systems on the cloud. The ideal candidate combines architectural leadership with hands-on proficiency in modern AI frameworks, and can translate complex business goals into innovative, AI-driven technical solutions.

Primary Stack and Tools:

  • Languages: Python, SQL, Bash
  • ML/AI Frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers.
  • GenAI & LLM Tooling: OpenAI APIs, LangChain, LlamaIndex, Cohere, Claude, Azure OpenAI.
  • Agentic & Multi-Agent Frameworks: LangGraph, CrewAI, Agno, AutoGen
  • Search & Retrieval: FAISS, Pinecone, Weaviate, Elasticsearch
  • Cloud Platforms: AWS, GCP, Azure (preferred: Vertex AI, SageMaker, Bedrock)
  • MLOps & DevOps: MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines, Terraform, FAST API
  • Data Tools: Snowflake, BigQuery, Spark, Airflow.

Key Responsibilities:

  • Architect scalable and secure AI systems leveraging LLMs, GenAI, and multi-agent frameworks to support diverse enterprise use cases (e.g., automation, personalization, intelligent search).
  • Design and oversee implementation of retrieval-augmented generation (RAG) pipelines integrating vector databases, LLMs, and proprietary knowledge bases.
  • Build robust agentic workflows using tools like LangGraph, CrewAI, or Agno, enabling autonomous task execution, planning, memory, and tool use.
  • Collaborate with product, engineering, and data teams to translate business requirements into architectural blueprints and technical roadmaps.
  • Define and enforce AI/ML infrastructure best practices, including security, scalability, observability, and model governance.
  • Manage technical roadmap, sprint cadence, and 3–5 AI engineers, coach on best practices.
  • Lead AI solution design reviews and ensure alignment with compliance, ethics, and responsible AI standards.
  • Evaluate emerging GenAI & agentic tools; run proofs-of-concept and guide build vs-buy decisions.

Qualifications:

  • 9+ years of experience in AI/ML engineering or data science, with 2+ years in AI architecture or system design.
  • Proven experience designing and deploying LLM-based solutions at scale, including fine-tuning, prompt engineering, and RAG-based systems.
  • Strong understanding of agentic AI design principles, multi-agent orchestration, and tool-augmented LLMs.
  • Proficiency with cloud-native ML/AI services and infrastructure design across AWS, GCP, or Azure.
  • Deep expertise in model lifecycle management, MLOps, and deployment workflows (batch, real-time, streaming).
  • Familiarity with data governance, AI ethics, and security considerations in production-grade systems.
  • Excellent communication and leadership skills, with the ability to influence. technical and business stakeholders.

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