Senior AI Engineer

Job Post for

Senior AI Engineer

Location: Goregaon, Mumbai

Experience: 4-7 years of experience

Role:

We’re a product company specialising in Artificial Intelligence, Machine Learning, Data Analytics, and Cloud-based technologies. If you're passionate about architecting and delivering cutting-edge AI solutions at scale, this role will give you ownership across the full AI lifecycle. As a Senior AI Engineer, you will lead and collaborate with engineers, data scientists, and product teams to design, implement, and optimise AI-powered solutions, with significant hands-on work on Large Language Models (LLMs), machine learning workflows, and end-to-end AI product development.

Job Responsibilities:

• Model Development & Integration:
  Lead the design, development, and fine-tuning of LLMs and GenAI solutions such as enterprise chatbots, task-specific AI assistants, and ML-driven solutions for prediction, forecasting, and decision support.
• Solution Architecture: Define AI solution architectures, select appropriate models, frameworks, and tooling, and ensure robustness, scalability, observability, and security in production environments.
• Data Handling & MLOps: Oversee data collection, cleaning, preprocessing, and feature engineering; work closely with data engineers to set up reliable data pipelines and model retraining workflows.
• AI Frameworks:
  Build, evaluate, and optimise AI solutions using frameworks like LangChain, LangGraph, CrewAI, LlamaIndex, TensorFlow, and PyTorch, and drive best practices in prompt engineering, evaluation, and guard railing.
• Deployment & Productionization:
  Own or co-own deployment of models to production (APIs, microservices, or batch jobs), ensuring performance, cost efficiency, monitoring, and seamless integration with existing systems.
• Technical Leadership: Mentor junior AI engineers and interns, review code and design documents, and establish coding standards, experimentation practices, and documentation norms for the AI team.
• Collaboration: Partner with senior stakeholders, software developers (SDEs), product managers, and clients to translate business problems into AI solutions and drive them from concept to successful delivery.
• Research & Innovation: Continuously evaluate the latest developments in generative AI, NLP, ML, and LLMOps; run PoCs; and recommend new techniques, models, or tools that can improve product capabilities.
• Documentation & Communication: Maintain clear technical documentation, experiment logs, and architecture diagrams; present design choices, trade-offs, and results effectively to technical and non-technical audiences.

Skills & Qualifications

Education:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence
• Master’s degree or relevant certifications in AI/ML, data science, or cloud platforms is a plus.

Experience:

• 4–7 years of hands-on experience in AI/ML engineering, with at least some experience delivering production-grade AI or GenAI solutions end to end.
• Proven experience working with LLMs, NLP, and ML workflows in real-world projects.

Technical skills:

• Strong proficiency in Python and solid working knowledge of SQL.
• Ability to write clean, efficient, modular code following good coding and testing practices.
• Experience with Git/GitHub and modern development workflows (branching, PR reviews, CI).
• Hands-on experience building APIs and services using FastAPI (or similar) and creating internal tools/dashboards using Streamlit (or similar).
• Deep understanding of core ML concepts (supervised/unsupervised learning, evaluation metrics, feature engineering) and practical experience with NLP and GenAI solutions.
• Practical experience with one or more AI orchestration / LLM frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex.
• Strong experience with deep learning frameworks like TensorFlow and/or PyTorch for training, fine-tuning, and serving models.
• Exposure to MLOps concepts (model versioning, experiment tracking, monitoring, CI/CD for ML) is highly desirable.
• Familiarity with at least one major cloud platform (AWS, GCP, or Azure), including basic services for compute, storage, and AI/ML tooling.
• Ability to profile and optimise model performance (latency, throughput, cost).

Other skills:

• Strong analytical and problem-solving abilities, with a structured approach to debugging data, models, and systems.
• Attention to detail and a proactive, ownership-driven mindset.
• Good verbal and written communication skills, including the ability to explain complex AI concepts to non-technical stakeholders.
• Ability to work independently and collaboratively in a fast-paced, product-focused environment, managing multiple initiatives in parallel.
• Comfortable mentoring junior team members and contributing to a culture of learning and innovation.

Benefits:

• Actual salaries will vary depending on a candidate's experience, qualifications, skills and location.
• Medical Insurance
• Paid Leaves
• Flexible work schedules
• Development and career growth opportunities
• Open Time Off