Lead Engineer/Associate Architect - Data/AI

Description:

We are seeking an experienced Architect to drive our data and AI streams. The ideal candidates are not just technical experts but also strategic thinkers who can act as independent consultants, guiding projects from concept to production. They should have a proven track record of designing, developing, and deploying robust, scalable, and real-world AI systems.

Responsibilities:

• Architect and Design: Lead the architecture, design, and implementation of highly scalable and reliable data platforms and AI systems. This includes building foundational data pipelines, data lakes, and real-time data streams
• AI/ML Development: Drive the end-to-end lifecycle of machine learning models, from experimentation and feature engineering to deployment, monitoring, and maintenance in a production environment (MLOps)
• Technical Leadership: Act as a technical lead, mentoring junior engineers, setting best practices, and performing code reviews to ensure high-quality and efficient code
• Strategic Consultation: Work directly with our client’s technical and product teams to understand requirements and translate them into a clear technical vision and roadmap
• Innovation: Stay current with the latest advancements in AI, LLMs, machine learning, and data engineering to introduce new technologies and methodologies that improve our capabilities
• Collaboration: Partner with cross-functional teams, including product managers, data scientists, and software engineers, to deliver integrated solutions

Requirements

• Extensive Experience: 8+ years of hands-on experience in AI/ML and data engineering
• Scalable AI Systems: Proven experience designing and implementing scalable AI systems in a production environment. This includes a deep understanding of MLOps principles and tools
• Technical Expertise:
  • Data Technologies: Proficiency with modern data platforms and tools (e.g., Databricks, Snowflake, Apache Spark, Flink, Airflow, Kafka)
  • AI/ML Frameworks: Strong command of at least one major ML framework (e.g., TensorFlow, PyTorch). Experience with large language models (LLMs) and other generative AI technologies is a significant plus
  • Gen AI Frameworks: Exposure to LLMs like Open AI, Claude, Gemini etc and frameworks like LangChain, LangGraph, LangSmith, LangFlow etc
  • Programming Languages: Expert-level proficiency in at least one key programming language (e.g., Python, Scala, Java)
• Cloud Platforms: Extensive experience with one or more major cloud providers (AWS, GCP, or Azure), including their data and AI services
• Data Engineering : Exposure to big data processing using PySpark or Databricks is an added advantage while not a mandatory skill
• Problem-Solving: Exceptional analytical and problem-solving skills, with the ability to tackle complex, ambiguous challenges independently
• Communication: Excellent communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders

Preferred Qualifications:

• Experience with a diverse set of AI applications, such as computer vision, natural language processing, or time-series analysis
• Background in an industry with complex data requirements (e.g., finance, e-commerce, healthcare)
• A portfolio of open-source contributions demonstrating real-world projects and technical depth