Job Title: AI PoC Engineer
Location: Mumbai - 1 day a week
Reports To: Vice President (Cloud, API & DevOps)
Duration: Contract to Hire
Salary: 25-35 LPA
Job Description
We are looking for a highly skilled AI POC Engineer to design, develop, and validate AI/ML proof-of-concepts (POCs) that demonstrate the feasibility and value of AI-driven solutions. The ideal candidate will have strong expertise in machine learning, generative AI, and cloud-based AI services to rapidly prototype and evaluate innovative use cases.
This role focuses on building AI agents, RAG pipelines, finetuning LLMs, and rapidly prototyping solutions alongside an experienced AI team.
Key Responsibilities
- Design, build, and validate AI/ML and generative AI POCs to assess feasibility and business impact.
- Leverage pre-trained models, APIs (Azure OpenAI, Gemini, Hugging Face, etc.), and custom ML models for quick iterations.
- Work with structured and unstructured data (text, images, audio, etc.) to clean, preprocess, and engineer features for POCs.
- Ensure data privacy, compliance, and ethical AI practices.
- Experiment with LLMs, computer vision, NLP, or predictive analytics models to determine optimal approaches.
- Evaluate models for accuracy, scalability, latency, and cost-effectiveness.
- Develop APIs or scripts to integrate POCs with existing systems, cloud services, or pipelines.
- Collaborate with DevOps/MLOps teams to transition successful POCs into production-ready pipelines.
- Utilize Azure native AI services for rapid experimentation.
- Prepare clear documentation of methodologies, results, and next steps for business and technical stakeholders.
- Conduct demos and workshops to showcase AI capabilities and findings.
Qualifications
- Bachelor's or master's degree in computer science, Data Science, AI, or related field.
- 36+ years of experience in AI/ML development, data science, or applied research.
- Strong programming skills in Python or .Net
- Hands-on experience with LLMs, NLP, or computer vision techniques.
- Experience with at least one cloud AI platforms (Azure AI, AWS AI, or GCP Vertex AI).
- Familiarity with prompt engineering, vector databases, and RAG pipelines.
- Experience in generative AI (text, image, or audio) and fine-tuning LLMs.
- Understanding of MLOps principles for scaling successful POCs.
- Exposure to data privacy, security, and responsible AI practices.
- Relevant certifications (e.g., Azure AI Engineer Associate, Google Cloud ML Engineer).
