Artificial Intelligence Engineer

Role : Artificial Intelligence Engineer

Location : Navi Mumbai (Hybrid)

Experience : 35 Years

Company : Focalworks Solutions Pvt Ltd

About Us :

Focalworks is a trusted digital solutions partner for global organizations, consulting firms, and startups. Since 2008, we have been passionate about creating impact through technology, crafting custom software, digital experiences, and e-commerce solutions that drive success. As we look to the future, we are building the next generation of AI-powered solutions to lead the charge in digital transformation. We believe this is the future of software, and we are looking for brilliant engineers to join us in this exciting venture.

The Role :

We are seeking a skilled AI Engineer with a strong software engineering background to be a key player in our AI-Solutions team. You will be responsible for designing, developing, and deploying intelligent systems that solve real-world business problems and power consumer applications of the future.

Key Responsibilities (What You Will Do and Master) :

- 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.

Required Qualifications (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 practiced the fundamentals of crafting effective prompts to guide and steer LLM behavior.

- 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.

Essential Soft Skills :

- 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 :

- A competitive salary and performance bonus.

- Comprehensive health insurance.

- 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.