Senior AI/ML & Generative AI Engineer

About the Role

WOW Softech is looking for a seasoned Senior AI/ML & Generative AI Engineer to join its team in Hyderabad, with the role also mentioning Bangalore as a work location. The position suits professionals with deep hands-on experience in building, deploying, and scaling AI-driven solutions for enterprise environments. The company is described as one of the Big 4 companies.

What You’ll Do

• Create and roll out scalable machine learning and generative AI solutions for complex business problems.
• Develop enterprise-grade applications using large language models and related AI techniques.
• Build AI agents and assistants with orchestration tools such as LangChain.
• Use GitHub Copilot, Gemini, and similar AI development tools to speed up software delivery and improve developer productivity.
• Connect GenAI capabilities to business systems through APIs, vector stores, and cloud services.
• Design retrieval-augmented generation workflows for knowledge management and conversational AI use cases.
• Refine, test, and track LLM outputs to maintain quality, reliability, and scale.
• Partner with cross-functional teams to convert business needs into AI-based solutions.
• Handle data preparation, feature creation, training, validation, and deployment steps end to end.
• Develop strong analytical pipelines in Python and/or R for experimentation and production use.
• Integrate AI solutions with major cloud platforms while following security and governance requirements.
• Review code, define engineering standards, and guide junior team members.
• Keep pace with new developments in AI, generative AI, agent frameworks, and cloud technologies.

Experience Needed

• 6 to 8.5 years of total experience in software engineering, data science, or AI/ML work.
• At least 2–3 years of direct experience building Generative AI and LLM-based applications.

Technical Background

• Strong grounding in machine learning and deep learning concepts.
• Experience designing and delivering Generative AI solutions.
• Practical knowledge of LLMs, including prompt engineering, evaluation, and optimization.
• Hands-on exposure to retrieval-augmented generation workflows.
• Experience developing AI assistants, agents, and orchestration flows using frameworks like LangChain.
• Familiarity with function calling, tool integration, and conversational AI systems.
• Working knowledge of GitHub Copilot, Gemini, and other AI-assisted development platforms.
• Solid programming skills in Python and R.
• Experience with analytical and ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch.
• Experience integrating AI systems with AWS, Azure, or Google Cloud Platform.
• Understanding of REST APIs, Docker-based containerization, CI/CD, and cloud-native deployment.
• Familiarity with SQL and NoSQL systems, vector databases, and ETL/data pipeline concepts.

Preferred Profile

• Experience deploying models with MLflow, Kubernetes, or broader MLOps practices.
• Exposure to multi-agent architectures and autonomous AI workflows.
• Knowledge of responsible AI, governance, and AI security practices.
• Cloud or AI/ML certifications are an added advantage.
• Prior work in Agile or Scrum environments is preferred.

Education

A bachelor’s or master’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related discipline is preferred. The eligibility note provided specifies B.Tech / B.E. in any specialization.

Candidate Profile

• Strong reasoning and problem-solving ability.
• Good communication and stakeholder handling skills.
• Comfort working independently in a fast-moving environment.
• Genuine interest in innovation and continuous learning in emerging AI areas.
• Proven ability to deliver production-ready AI solutions with measurable business value.

Keywords

Generative AI, GenAI, LLMs, LangChain, AI agents, AI assistants, GitHub Copilot, Gemini, prompt engineering, RAG, Python, R, machine learning, deep learning, vector databases, MLOps, AWS, Azure, GCP, TensorFlow, PyTorch, Scikit-learn, conversational AI, agentic AI.