Technical Lead - AI & Data System

Job Title : Tech Lead - AI & Data Systems

Experience : 3 - 7 Years

Role Type : Full-Time

Permanent Function : Engineering / AI & Data Platforms

Role Overview :

We are looking for a Tech Lead AI & Data Systems to design, build, and scale intelligent data-driven platforms. This role requires a strong blend of hands-on engineering, AI/ML system design, and technical leadership. The ideal candidate will drive end-to-end development of AI-powered data solutions while mentoring engineers and collaborating closely with product, analytics, and business stakeholders.

Key Responsibilities :

AI & Data Platform Engineering :

- Design, develop, and deploy scalable AI/ML-enabled data systems supporting analytics, prediction, and automation use cases.

- Build and optimize data pipelines (batch & real-time) for ingestion, processing, and transformation of structured and unstructured data.

- Lead the integration of ML models into production systems, ensuring reliability, performance, and scalability.

- Implement feature engineering pipelines, model inference workflows, and monitoring mechanisms.

Machine Learning & AI Systems :

- Develop and productionize ML models using frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.

- Work on ML lifecycle management (MLOps) including model versioning, deployment, retraining, and performance tracking.

- Apply AI techniques such as : Predictive modeling NLP / Computer Vision (where applicable) Recommendation systems Anomaly detection Ensure models are explainable, measurable, and aligned with business outcomes.

Data Architecture & Engineering :

- Design data architectures using data lakes, data warehouses, and streaming systems.

- Work with technologies such as SQL/NoSQL databases, Spark, Kafka, Airflow, Snowflake/BigQuery/Redshift.

- Ensure data quality, governance, and security across the data ecosystem.

- Optimize data storage, query performance, and cost efficiency.

Technical Leadership :

- Act as a technical owner for AI & data initiatives from design to deployment.

- Review architecture, code, and system designs to enforce best practices.

- Mentor junior engineers and guide them on system design, ML concepts, and coding standards.

- Collaborate with Product, Analytics, and Business teams to translate requirements into scalable technical solutions.

Cloud & DevOps :

- Build and deploy AI/data systems on cloud platforms (AWS, Azure, or GCP).

- Implement CI/CD pipelines for data and ML workflows. Use containerization and orchestration tools such as Docker and Kubernetes.

- Monitor system performance, reliability, and scalability in production.

Required Skills & Qualifications :

- 3- 7 years of experience in data engineering, AI/ML systems, or backend engineering.

- Strong programming skills in Python (mandatory); familiarity with Java/Scala is a plus.

- Hands-on experience with machine learning model development and deployment.

- Solid understanding of data structures, algorithms, and distributed systems.

- Experience working with big data frameworks (Spark, Hadoop) and streaming platforms.

- Strong SQL skills and experience with both relational and NoSQL databases.

- Knowledge of MLOps, model monitoring, and ML pipeline automation.

- Experience with cloud-native data and ML services.

- Familiarity with tools such as Airflow, MLflow, Kubeflow, SageMaker, Vertex AI, or equivalents.

- Exposure to monitoring, logging, and alerting tools.

Preferred / Good-to-Have Skills :

- Experience with Generative AI, LLMs, embeddings, or vector databases.

- Knowledge of data governance, privacy, and compliance frameworks.

- Exposure to real-time analytics and event-driven architectures.

- Prior experience working in Agile/Scrum environments.

- Startup or fast-scaling product company experience.