Name of the Post : Artificial Intelligence (AI) Engineer

Type of the Post :Contractual on Full Time basis.

Number of Posts: 4 (Four)

Place of Posting: Chennai / Lucknow

Period of Contract :The Term of Contract would initially be for a period of Three (03) years, extendable, at sole discretion, for a further period of up to Two (02) years. The Contract can be terminated at Two (02) months of notice on either side or salary and allowances (if any) in lieu thereof.

Eligibility Criteria/Age Limit:

The Candidate should not be more than 40 years old as of the last date of submission of application.

Educational Qualification:

Graduation in Engineering / B.E. / B. Tech / M.S. / M. Tech / M. Sc. (Computer Science / Computer Science and Engineering / Information Technology / Electronics / Electronics and Communication Engineering / Data Science/AI/ML) or Equivalent Degree in above specified disciplines OR Masters Degree in Statistics, Mathematics, Economics, Computer Science, Data Science OR MCA from University / Institution / Board recognized by Government of India.

Preferred Certifications: Certifications in Data Science / Machine Learning / AI etc.

Experience:

Minimum Eight (08) years of relevant experience with minimum Four (04) years of experience in the role of AI Engineers, Data Science, Building Statistical Models
Experience in Banking and Finance Domain will be an added advantage.

Job Profile:

Understand Business Requirements and identify opportunities for Artificial Intelligence (AI), Machine Learning (ML), Data Science.
Analyse various data sources and look at best available ways in automating collection processes for usage of them in arriving at solutions.
Explore relevant data sources available in the market.
Undertake pre-processing of structured and unstructured data. Analyse large datasets to discover trends and patterns.
Build and Enhance Custom Data Models keeping in mind accuracy and performance of output.
Use predictive modelling to increase / improve user experience.
Develop processes and tools to monitor model performance and data accuracy.
Present information using data visualization techniques.
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Develop custom data models and algorithms to apply to data sets.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Development / Coding in NLP, R, Python etc. and other evolving technologies in data management.




Develop processes and tools to monitor model performance and data accuracy.
Present information using data visualization techniques.

Key Skills:

Minimum Fifteen (08) years of relevant experience with minimum Four (04) years of experience in the role of AI Engineers, Data Science, Building Statistical Models
Development and Coding Proficiency in Python / R
Proficiency in Statistical Skills including knowledge of statistical tests, data distributions, Proficiency of ML Algorithms like Linear Regression, Logistic Regression, Decision Tree etc.
Good experience on working in Big Data Sets with tools like Apache Spark, SAS.
Valuable experience in Data Mining techniques and tools like Apache Mahout, H2O, Oracle Data Mining.
Good implementation knowledge of Data Modelling and Optimization techniques.
Good experience in Data frameworks like Hadoop, Database query languages like SQL, Hive and Data wrangling tools like Talend.
Exposure to BI Tools like Power BI, Tableau.
Designing functional technology solutions with core focus on process digitization and automation.
Build, validate and maintain statistical, ML and AI/GenAI models (e.g. credit scoring, PD/LGD, early warning, fraud detection, segmentation, pricing, impact/ESG scoring, text analytics) using structured and unstructured data.
Work with Data Engineers and IT teams to productionise models through APIs, batch pipelines or decision engines, ensuring performance, scalability and monitoring.
Ensure model explainability, fairness, and compliance with RBI and internal governance norms.
Monitor model performance and refine algorithms for accuracy and stability.
Explore and evaluate new AI tools, techniques, and technologies.
Prepare documentation and support knowledge sharing across verticals.
Convert prototype notebooks and POCs into robust, modular services or APIs integrated with core banking, LOS/LMS, collections systems, digital channels and partner/fintech platforms.

Secondary Skills:

Good programming Skills and analytical abilities.
Functional knowledge in ML techniques and tools like TensorFlow, Apache Mx Net etc.
Certifications associated to AI/ML will be an added advantage.
Financial Domain knowledge is another advantage.




Establish model monitoring for drift, latency, throughput, failures and key business. metrics; work with data scientists and business owners to trigger retraining or model refresh.
Collaborate with Information Security and IT to ensure ML services meet security, compliance, logging and audit requirements.
Using statistical / ML libraries and tools such as Python (pandas, scikitlearn etc.), R, or similar environments, experience with notebooks and version control.
Working with large financialservices datasets, data cleaning, feature engineering, and collaborating with data engineering / IT teams to operationalise solutions.
AI/ML Solutions with knowledge in Deep Learning Techniques.
Experience in Application Architecture and Design.
Experience in AI/ML Solutions with knowledge in Deep Learning Techniques.
Experience with cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and integrating AI models into production systems (e.g., via APIs, microservices).
Building and deploying ML models into production (APIs, batch jobs, streaming) using Python/Java/Scala and standard frameworks.
Working with cloud platforms, containers (Docker), orchestration (Kubernetes) and CI/CD pipelines.
Optimising model inference performance, managing environments, dependencies and monitoring in Production.

Competency:

Mining, Processing, Cleansing and Validating integrity of data to be used for analysis.
Usage of Statistics and ML Algorithms to arrive at custom data models to provide accurate outputs.
Analyse large amounts of information to find patterns and solutions.
Usage of Statistics and ML Algorithms to arrive at custom data models to provide accurate outputs.
Resolve complex technical issues in implementation of ML Solutions.
Excellent Verbal and Written - Communication and Presentation Skills.
Statistical, ML and GenAI modelling (Proficient): Strong grounding in statistics, probability, hypothesis testing, regression, classification, clustering, timeseries, basic optimisation and applied GenAI/NLP techniques (LLMs, embeddings, prompt design), with a proven modelbuilding and deployment track record
GenAI / advanced analytics (Basic to Intermediate): Exposure to NLP, embeddings, LLMbased applications, or recommendation systems relevant to MSME banking and development programmes
Data Engineering (Proficient): ETL pipelines, feature engineering, handling structured/unstructured data (e.g., Pandas, Spark, SQL).
Domain Knowledge (Intermediate): Financial services use cases (credit scoring, fraud, customer insights); familiarity with RBI guidelines on AI/ML.

📌 Artificial Intelligence Engineer (Uttar Pradesh)
🏢 National Institute for Smart Government (NISG)
📍 Uttar Pradesh