Lead AI Egnineer

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.

Lead Consultant – Data & AI

Role Overview:

hands-on technical leader

• 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.