AI Engineer – Generative AI

Focalworks Solutions Private Limited; Mumbai; On-site; INR 1,200,000 - 1,600,000; Full time

Benefits offered by this job

Competitive salary with performance-linked bonus

Flexible working hours

Professional development budget

Diverse AI project opportunities

Job summary

A leading tech company is looking for AI Engineers with 3-5 years of experience in Generative AI. The role involves building advanced AI agents, mastering systematic prompt engineering, and integrating real-world tools and APIs. Candidates should have solid proficiency in Python, machine learning concepts, and experience with modern frameworks like PyTorch and TensorFlow. The company offers a competitive salary, performance bonuses, and a hybrid work model, along with opportunities for professional development.

Qualifications

• 3-5 years of experience in Generative AI.
• Solid understanding of machine learning and deep learning.
• Experience with data processing and refinement.
• Familiarity with modern AI applications.
• Experience in building RESTful APIs.

Responsibilities

• Build advanced AI agents capable of reasoning and executing tasks.
• Implement tool and API integration for real-world actions.
• Develop systematic prompt engineering techniques.
• Drive rigorous evaluation and experimentation for AI performance.
• Implement safety and guardrails for reliable agent operations.
• Take ownership of production AI components.

Skills

Python proficiency

Machine learning concepts

Deep learning concepts

Prompt engineering

Clear communication

Tools

PyTorch

TensorFlow

Hugging Face

LangChain

LlamaIndex

Job description

AI Engineers with 3 – 5 years of relevant experience in Generative AI

You’ll need to be a hands-on problem-solver at the intersection of software engineering and AI. This role requires deep technical curiosity, experience with modern LLM stacks, and a strong grasp of foundational AI concepts, as well as advanced prompt engineering practices.

What you’ll do:

• Build Advanced AI Agents: Move beyond simple chains to develop complex, multi-step AI agents that can reason, plan, and execute tasks. You’ll become an expert in advanced architectural patterns, orchestrating both deterministic and non-deterministic workflows, and exploring techniques like reinforcement learning to refine agent policies.
• Implement Deep Tool & API Integration: Equip agents with the ability to perform real-world actions by implementing Tool Calling and MCPs, and integrating them with a diverse set of internal and external tools, databases, and APIs.
• Master Systematic Prompt Engineering: Design sophisticated prompt chains using techniques like Chain-of-Thought and ReAct, and build systems to test, version, and manage these prompts like code.
• Drive Rigorous Evaluation & Experimentation: Develop automated evaluation suites to benchmark agent performance on metrics like correctness, relevance, and safety, driving continuous improvement through data-driven A/B testing.
• Implement Safety & Guardrails: Build critical safety layers and validation steps to ensure agents operate reliably and prevent them from taking unintended, incorrect, or harmful actions.
• Own AI System Observability & Optimization: Implement comprehensive logging, metrics, and tracing to monitor AI systems in production. Manage the trade-offs between performance, latency, and cost by implementing techniques like multi-LLM routing and advanced caching.
• Lead Enterprise-Scale System Ownership: Take true ownership of production AI components, ensuring their security, reliability, and scalability as part of our robust microservices architecture.

What you should have:

Core AI & Software Fundamentals

• Solid Python Proficiency: Expertise in Python and its ecosystem, including libraries like NumPy and Pandas.
• Machine Learning & Deep Learning Concepts: Have a solid grasp of the machine learning landscape, including common model types and when to apply them. You should be proficient in at least one major ML framework like PyTorch or TensorFlow .
• Data Processing & Refinement: Have practical experience with the day-to-day work of cleaning, preprocessing, and transforming structured and unstructured data to make it suitable for AI models.
• Broad AI Application Knowledge: Understand the principles behind a range of modern AI applications, such as semantic search, text summarization, chatbots, data extraction from unstructured text, and computer vision tasks like image analysis and object detection.
• API Development Experience: Have hands-on experience building, testing, and deploying RESTful APIs .

Core Generative AI Proficiency

• Prompt Engineering: Context Engineering: Understand the critical practice of strategically managing the information provided in an LLM’s context window. You understand and have practised the fundamentals of crafting effective prompts to guide and steer LLM behaviour. This includes using patterns like Retrieval-Augmented Generation (RAG), managing conversational history, and providing effective few-shot examples to ground the model and improve response quality.
• Understanding of LLMs and the Ecosystem: Have a strong grasp of how Large Language Models work, their capabilities, and their limitations. You are familiar with the Hugging Face ecosystem.
• Hands-on Experience with LLM Frameworks: Have built projects using modern LLM application frameworks (e.g., LangChain , LlamaIndex ).
• Knowledge of Fine-Tuning: Understand the concepts and use cases for adapting models to specific domains through fine-tuning.
• Production Deployment of GenAI (nice to have): Have some experience deploying Generative AI solutions to a production environment and understand the unique considerations involved, such as managing latency, optimizing costs, ensuring security, and monitoring for performance degradation or model drift.

What would be great to have:

• Strong Problem-Solving Mindset: You are naturally curious and adept at breaking down complex, ambiguous problems into manageable steps.
• Clear Communication: You can articulate technical concepts and decisions clearly to your peers.

What we offer:

• Competitive salary with performance-linked bonus
• A competitive salary and performance bonus.
• Flexible working hours and a hybrid work model.
• A budget for professional development, conferences, and certifications.
• The opportunity to work on diverse AI projects in a company with a 15+ year history of excellence.