We are looking for a Senior AI Engineer with strong hands-on experience in designing, building, deploying, and operating AI systems in production. The ideal candidate should have built AI/ML or GenAI solutions from the ground up, including architecture, model development, data pipelines, APIs, deployment, monitoring, and continuous improvement. This role requires someone who can work across the full AI lifecycle — from problem discovery and solution design to production-grade implementation — while collaborating closely with business users, data teams, engineering teams, and platform stakeholders.

Key Responsibilities

- Design and build end-to-end AI, Machine Learning, and Generative AI solutions from scratch.
- Translate business problems into scalable AI system designs and technical implementation plans.
- Develop and deploy production-ready AI applications, including APIs, backend services, workflows, and user-facing AI features.
- Build and maintain data pipelines required for model training, inference, evaluation, and monitoring.
- Implement LLM-based solutions using RAG, prompt engineering, agentic workflows, embeddings, vector databases, and orchestration frameworks.
- Evaluate, fine-tune, and optimize models for accuracy, latency, cost, reliability, and business impact.
- Design secure and governed AI systems with proper access control, data privacy, auditability, and responsible AI practices.
- Deploy AI workloads on cloud or containerized platforms using CI/CD, Docker, Kubernetes, and MLOps/LLMOps practices.
- Monitor production AI systems for performance drift, hallucination risks, failures, cost anomalies, and user adoption.
- Collaborate with product owners, data engineers, software engineers, architects, and business teams to deliver measurable outcomes.
- Create technical documentation, architecture diagrams, deployment guides, and operational runbooks.




- Mentor junior engineers and support best practices in AI engineering, code quality, testing, and production operations.

EDUCATION & QUALIFICATIONS

- Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, or a related discipline.
- Equivalent hands-on industry experience will also be considered.

REQUIRED SKILLS (explicitly call out must-have and nice-to-have skills expectations)

Relevant Skills and Experience:

- 7+ years of overall experience in software engineering, data engineering, AI engineering, or machine learning engineering.
- 3+ years of hands-on experience building AI/ML or GenAI systems for real-world business use cases.
- Proven experience taking AI systems from concept to production.
- Strong programming skills in Python, with experience in frameworks such as FastAPI, Flask, PyTorch, TensorFlow, scikit-learn, or similar.
- Experience with LLMs, RAG architectures, prompt engineering, embeddings, vector search, and AI orchestration frameworks.
- Hands-on experience with tools such as LangChain, LlamaIndex, MLflow,
- OpenAI/Azure OpenAI, Anthropic, Hugging Face, or equivalent platforms.
- Strong understanding of data pipelines, feature engineering, model evaluation, inference pipelines and model monitoring.
- Experience deploying applications using Docker, Kubernetes, CI/CD pipelines, and cloud services.
- Good knowledge of cloud platforms such as AWS, Azure, or GCP.
- Strong understanding of APIs, microservices,



event-driven architecture, and productiongrade system design.
- Experience with databases, data lakes, warehouses, and vector databases.
- Ability to write clean, modular, testable, and maintainable code.
- Solid problem-solving skills and ability to work with ambiguous business requirements.

Preferred Skills

- Experience with enterprise AI platforms, LLMOps, MLOps, or data platforms such as Databricks, Snowflake, Azure ML, SageMaker, Vertex AI, or similar.
- Experience building AI agents, workflow automation, decision-support systems, or intelligent assistants.
- Knowledge of model governance, responsible AI, data privacy, security, and compliance requirements.
- Experience with real-time or near-real-time AI inference systems.
- Exposure to operational domains such as aviation, logistics, supply chain, workforce planning, customer operations, or enterprise analytics.
- Experience optimizing GenAI solutions for cost, latency, accuracy, and reliability.
- Familiarity with observability tools, logging, tracing, model monitoring, and production support processes.

IDEAL CANDIDATE PROFILE & PREFERENCES The ideal candidate is a hands-on builder who has successfully designed and delivered AI systems in production, not just prototypes or proof-of-concepts. They should be comfortable working across architecture, engineering, data, models, deployment, monitoring, and business stakeholder engagement. They should be able to take ownership of complex AI initiatives, make practical technology choices, and deliver reliable AI solutions that solve real business problems at scale. Pay: ₹1,500,000.00 - ₹2,800,000.00 per year

Application Question(s)

- Immediate to 15 days preferred

Experience:
- data engineering: 7 years (Preferred)
- Machine learning: 3 years (Preferred)

Work Location: In person

📌 AI Engineer (Bengaluru)
🏢 Sama
📍 Bengaluru