Lead Data Scientist/AI Engineer

Job description

Founded in 2017, CoffeeBeans specializes in offering high-end consulting services in technology, product, and processes.

We help our clients attain significant improvement in quality of delivery through impactful product launches, process simplification, and help build competencies that drive business outcomes across industries.

The company uses new-age technologies to help its clients build superior products and realize better customer value.

We also offer data-driven solutions and AI-based products for businesses operating in a wide range of product categories and service domains.

At CoffeeBeans Consulting, we are a dynamic software consulting firm helping clients solve complex problems through innovative technology solutions.

We’re expanding our Data & AI practice and looking for a Lead Consultant – Data & AI to help us build and deliver high-impact data and AI projects for our clients.

Role Overview:

We’re looking for a hands-on technical leader who combines deep expertise in AI/ML (traditional ML and GenAI) with strong skills in modern data engineering and architecture.

This role is:

• Hands-on engineering and architecture, building and implementing solutions.

• Client-facing consulting, understanding business problems and translating them into technical solutions.

• Mentoring and guiding junior team members, fostering a high-performance team culture.

You will work closely with clients to design, build, and deliver impactful Data & AI solutions while establishing best practices and maintaining a high bar for technical quality.

Key Responsibilities:

Solution Design & Delivery

• Architect and implement end-to-end AI/ML solutions, including:

• Data pipelines and scalable data architectures.

• Traditional ML models and workflows.

• GenAI and agentic AI systems, including retrieval-augmented generation (RAG) and LLM-based applications.

• Ensure delivery of high-quality, scalable, and maintainable solutions aligned with client needs.

• Establish and advocate best practices for MLOps and data engineering workflows.

Consulting & Client Engagement

• Act as a trusted technical advisor for clients, shaping their Data & AI strategy and roadmaps.

• Translate business problems into technical solutions with clear articulation of value.

• Facilitate technical discussions and workshops with stakeholders to gather requirements and guide solutions.

Technical Leadership

• Lead by example, contributing hands-on to critical parts of projects.

• Set code and architectural standards for AI and data projects.

• Stay current with industry trends and advancements in AI/ML, GenAI, and data engineering.

Team Development

• Mentor and upskill junior engineers and data scientists within the team.

• Foster a collaborative, inclusive, and supportive team environment.

• Support the hiring and onboarding of new team members as we grow our Data & AI capability.

Key Requirements:

✅ Experience:

• ~10–12 years in the software/technology industry.

• Minimum 5+ years of experience designing and building AI/ML solutions in production environments.

• Strong experience with data engineering and architecture in production systems.

• Experience working in consulting or client-facing delivery environments.

✅ Technical Skills:

• Deep knowledge of traditional ML (classification, regression, NLP, computer vision) and GenAI (LLMs, embeddings, RAG, agentic AI workflows).

• Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, LangChain/LlamaIndex).

• Proficiency in Python (and/or R, Scala) for data and AI workloads.

• Experience with data engineering tools and orchestration frameworks (Spark, Databricks, Kafka, Airflow).

• Strong familiarity with cloud platforms (AWS, GCP, Azure) for deploying AI and data solutions.

• Understanding of MLOps practices (CI/CD for ML, monitoring, model retraining pipelines).

• Experience with data modeling, data lakes, and data pipeline architecture.

✅ Leadership & Mindset:

• Ability to lead and mentor technical teams in delivery environments.

• A consulting mindset with the ability to communicate effectively with technical and non-technical stakeholders.

• Empathetic leadership style, fostering trust and team growth.

• Comfortable in fast-paced, dynamic, client-facing environments.

Nice to Have:

• Experience with LLM fine-tuning and optimization.

• Strong hands-on experience with Databricks for scalable data and AI workloads.

• Exposure to agentic AI frameworks and advanced orchestration for LLM-powered workflows.

• Certifications in cloud or AI/ML specializations.

• Experience in growing Data & AI teams within a consulting environment.

Why Join Us?

• Opportunity to shape and expand our Data & AI practice from the ground up.

• Work with diverse clients to solve meaningful and challenging problems.

• Be part of a collaborative, people-first culture with a focus on growth and learning.

Competitive compensation and career advancement opportunities.

Required Skill Profession

Mathematical Science Occupations