At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior AI Engineer with a strong foundation in Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs) Large Language Models (LLMs). We are also looking for him to be a full-stack Engineer with hands-on experience with mobile front-end hands-on experience with mobile front-end Flutter, React-native. This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

• Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
• Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
• Hands on experience with mobile front-end Flutter, React-native etc.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
• Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
• Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
• Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
• Monitor and optimize service performance, reliability, and scalability in production environments.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

• 5+ years of overall experience mobile front-end Flutter, React-native etc
• 2+ years of experience in developing and deploying machine learning models and AI products in production environments.
• Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
• Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
• Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
• Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
• Background in building microservices or backend systems for data-rich AI/ML platforms.
• Experience with vector databases, embedding services, or semantic search integration.
• Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
• Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

• Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
• A flexible hybrid work model in our Bangalore office.
• Competitive compensation with performance-based rewards.
• A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

• Health & Wellness:
  • Comprehensive Group medical insurance including your parents with additional top-up options.
  • Accidental Insurance
  • Life insurance
  • Free online unlimited doctor consultations
  • An Employee Assistance Program (EAP)
• Work-Life Balance:
  • 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
  • 26 weeks of maternity leave, 15 days of paternity leave
  • Very unique to Reltio - 01 week of additional off as recharge week every year globally
• Support for home office setup:
  • Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
• No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

Job Description – Data Engineer

About the Role

We are looking for a  candidate who is  passionate about building scalable data pipelines, optimizing data workflows, and ensuring high data quality across systems. Candidates should demonstrate strong technical foundations, the ability to work independently, and a willingness to collaborate in a dynamic environment.

Core Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines to support business and analytical needs.
• Work extensively with Databricks, Python, and PySpark to process large datasets.
• Build and manage DAGs using Apache Airflow for workflow orchestration.
• Collaborate with cross-functional teams to understand data requirements and translate them into efficient engineering solutions.
• Develop and optimize complex SQL queries and participate in data modeling activities for relational and cloud data warehouses.
• Work with Amazon S3 for data storage, ingestion, partitioning, and integration within broader data lake and pipeline ecosystems.
• Ensure high standards of data quality, reliability, and performance across all data processes.
• Contribute to documentation, best practices, and continuous improvement initiatives.

Core Technical Requirements

1. Python Programming

• Strong experience writing clean, efficient Python code for data manipulation, automation, scripting, and ETL workflows.
• Familiarity with widely used data libraries (e.g., pandas, numpy).

1. Databricks

• Hands-on experience with Databricks for distributed data processing.
• Proficiency in PySpark, Delta Lake, notebooks, and building scalable pipelines.

1. Orchestration Tools

• Apache Airflow (Required): Ability to design, implement, and maintain complex DAGs for scheduling and orchestrating workflows.
• Argo Workflows (Preferred): Experience with Kubernetes-native orchestration platforms is an added advantage.

1. SQL Skills

• Advanced SQL expertise including writing complex queries, query optimization, and working with relational/cloud data warehouses.
• Experience in data modeling and performance tuning.

1. Cloud Storage (Amazon S3)

• Practical knowledge of S3 for ingestion, storage, data partitioning, access control, and integration as part of data lake architectures.

Experience Level

 2–5 years in Data Engineering or related roles..

Preferred Personal Attributes

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, evolving environment.

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior Backend Engineer with a strong foundation in Java, solid Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs). This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

• Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
• Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
• Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
• Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
• Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
• Monitor and optimize service performance, reliability, and scalability in production environments.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

• 5+ years of overall experience in backend engineering, with strong proficiency in Java for scalable, distributed systems.
• 2+ years of experience in developing and deploying machine learning models and AI products in production environments.
• Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
• Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
• Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
• Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
• Background in building microservices or backend systems for data-rich AI/ML platforms.
• Experience with vector databases, embedding services, or semantic search integration.
• Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
• Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

• Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
• A flexible hybrid work model in our Bangalore office.
• Competitive compensation with performance-based rewards.
• A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

• Health & Wellness:
  • Comprehensive Group medical insurance including your parents with additional top-up options.
  • Accidental Insurance
  • Life insurance
  • Free online unlimited doctor consultations
  • An Employee Assistance Program (EAP)
• Work-Life Balance:
  • 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
  • 26 weeks of maternity leave, 15 days of paternity leave
  • Very unique to Reltio - 01 week of additional off as recharge week every year globally
• Support for home office setup:
  • Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
• No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

Senior AI SDET (AI Engineering & Quality)

Location: Bengaluru, India – Hybrid

About Reltio

Reltio's AI-powered data unification and management platform—spanning entity resolution, multi-domain master data management (MDM), and data products—transforms siloed data from disparate sources into unified, trusted, and interoperable data. The Reltio Connected Data Platform™ delivers data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands across industries rely on our award-winning, cloud-native MDM capabilities to improve efficiency, manage risk, and drive growth.

At Reltio, our values guide everything we do: Customer First, Better Together, Simplify and Share, Own It, and Always Better Than Yesterday. If you share these values, we invite you to join us.

Role Overview

We are looking for a powerhouse engineer who bridges AI development and automated validation. This is a builder-tester role — you will own the full lifecycle of AI features: from writing core Python logic for agentic workflows and tuning prompts, to architecting robust evaluation frameworks that ensure those systems are enterprise-ready.

Core Responsibilities

1. AI Development & Engineering

• Agentic Implementation: Design and implement autonomous agents using frameworks such as LangGraph, CrewAI, or AutoGen.
• Prompt Engineering: Own the prompt lifecycle — design, version, and tune system prompts to minimize hallucinations and maximize intent recognition.
• RAG Pipeline Development: Build and optimize Retrieval-Augmented Generation (RAG) components, including document ingestion, chunking strategies, and vector database indexing.
• Feature Prototyping: Rapidly prototype AI-driven features in Python to validate feasibility before full-scale integration.
• Data Curation: Build golden datasets and synthetic data generation scripts to train and evaluate models.

1. Advanced Validation & Quality Architecture

• Automated Evaluation (Eval-as-Code): Build automated pipelines to measure LLM performance across metrics such as faithfulness, relevancy, and toxicity.
• Non-Deterministic Testing: Develop strategies to test "fuzzy" outputs using LLM-assisted evaluation (using one LLM to grade another).
• Hybrid Framework Development: Design and maintain a dual-stack automation framework covering both backend/infrastructure and AI/ML validation.
• End-to-End Orchestration: Integrate AI tests into the MLOps pipeline so that every model deployment or prompt change triggers a full regression of the agent's reasoning capabilities.
• Mentorship & Standards: Serve as the team's subject matter expert, defining standards for writing inherently testable AI code.

Required Skills

AI & Data Science

• Python: Strong proficiency with Pandas, NumPy, LangChain, and LlamaIndex.
• LLMs: Hands-on experience with OpenAI, Anthropic, or open-source models (Mistral, Llama); solid understanding of temperature, top-p sampling, and tokenization.
• Vector Databases: Experience with Pinecone, Milvus, or Weaviate.
• AI Evals & Observability: Practical experience building LLM-judge evaluation pipelines.

Software Engineering & QA

• Production-Grade Code: Ability to write and review complex automation suites for distributed systems.
• Architecture: Familiarity with microservices, async processing (Kafka/RabbitMQ), and RESTful APIs.
• Performance Testing: Experience with JMeter or Locust to benchmark LLM inference latency and streaming responses.

What You Bring

• 5+ years of experience as an SDET, QA Automation Engineer, or AI Engineer.
• 2+ years of hands-on experience testing AI/ML products.
• Experience integrating AI tools and agents into quality lifecycle management.
• Proven ability to write and review production-quality code.
• Solid background in test case design, test planning, and issue lifecycle management in a continuous deployment environment.
• Experience working in agile environments and testing highly scalable SaaS applications.

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

Senior AI SDET (AI Engineering & Quality)

Location: Bengaluru, India – Hybrid

About Reltio

Reltio's AI-powered data unification and management platform—spanning entity resolution, multi-domain master data management (MDM), and data products—transforms siloed data from disparate sources into unified, trusted, and interoperable data. The Reltio Connected Data Platform™ delivers data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands across industries rely on our award-winning, cloud-native MDM capabilities to improve efficiency, manage risk, and drive growth.

At Reltio, our values guide everything we do: Customer First, Better Together, Simplify and Share, Own It, and Always Better Than Yesterday. If you share these values, we invite you to join us.

Role Overview

We are looking for a powerhouse engineer who bridges AI development and automated validation. This is a builder-tester role — you will own the full lifecycle of AI features: from writing core Python logic for agentic workflows and tuning prompts, to architecting robust evaluation frameworks that ensure those systems are enterprise-ready.

Core Responsibilities

1. AI Development & Engineering

• Agentic Implementation: Design and implement autonomous agents using frameworks such as LangGraph, CrewAI, or AutoGen.
• Prompt Engineering: Own the prompt lifecycle — design, version, and tune system prompts to minimize hallucinations and maximize intent recognition.
• RAG Pipeline Development: Build and optimize Retrieval-Augmented Generation (RAG) components, including document ingestion, chunking strategies, and vector database indexing.
• Feature Prototyping: Rapidly prototype AI-driven features in Python to validate feasibility before full-scale integration.
• Data Curation: Build golden datasets and synthetic data generation scripts to train and evaluate models.

1. Advanced Validation & Quality Architecture

• Automated Evaluation (Eval-as-Code): Build automated pipelines to measure LLM performance across metrics such as faithfulness, relevancy, and toxicity.
• Non-Deterministic Testing: Develop strategies to test "fuzzy" outputs using LLM-assisted evaluation (using one LLM to grade another).
• Hybrid Framework Development: Design and maintain a dual-stack automation framework covering both backend/infrastructure and AI/ML validation.
• End-to-End Orchestration: Integrate AI tests into the MLOps pipeline so that every model deployment or prompt change triggers a full regression of the agent's reasoning capabilities.
• Mentorship & Standards: Serve as the team's subject matter expert, defining standards for writing inherently testable AI code.

Required Skills

AI & Data Science

• Python: Strong proficiency with Pandas, NumPy, LangChain, and LlamaIndex.
• LLMs: Hands-on experience with OpenAI, Anthropic, or open-source models (Mistral, Llama); solid understanding of temperature, top-p sampling, and tokenization.
• Vector Databases: Experience with Pinecone, Milvus, or Weaviate.
• AI Evals & Observability: Practical experience building LLM-judge evaluation pipelines.

Software Engineering & QA

• Production-Grade Code: Ability to write and review complex automation suites for distributed systems.
• Architecture: Familiarity with microservices, async processing (Kafka/RabbitMQ), and RESTful APIs.
• Performance Testing: Experience with JMeter or Locust to benchmark LLM inference latency and streaming responses.

What You Bring

• 5+ years of experience as an SDET, QA Automation Engineer, or AI Engineer.
• 2+ years of hands-on experience testing AI/ML products.
• Experience integrating AI tools and agents into quality lifecycle management.
• Proven ability to write and review production-quality code.
• Solid background in test case design, test planning, and issue lifecycle management in a continuous deployment environment.
• Experience working in agile environments and testing highly scalable SaaS applications.

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, large-scale recommendation systems, and modern agentic AI systems.

You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

Classical ML & Recommendation Systems

• Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
• Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
• Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.

Agentic Systems & Next-Gen AI

• Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.

Cross-functional impact

• Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance’s consumer experiences.
• Contribute to Glance’s ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.

The experience we need

We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.

You should have experience with:

• Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
• Classical ML and deep learning techniques across NLP, sequence modeling, RL, clustering, and time series.
• Experience in deploying ML workflows/models in production system
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
• Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
• Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Comfortable working in cross-functional teams.
• Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
• Excellent communication skills with the ability to simplify complex technical concepts.

Job Description:

As part of our global Petro technical team, this role will predominantly focus on the Oil & Gas vertical, providing insights and expertise related to onshore U.S. opportunities. This position offers an exceptional opportunity for individuals looking to build their careers with an international firm and collaborate closely with veterans from top U.S. shale operators.

Responsibilities:

• Lead a team of reservoir engineers and analysts, ensuring timely due diligence on all deals evaluated by the firm, and manage other ongoing Petrotech projects.
• Conduct reservoir engineering analyses to assess the viability and profitability of oil and gas assets.
• Perform production analysis and forecasting across multiple onshore U.S. basins.
• Utilize proprietary software tools for production forecasting and performance evaluation.
• Deconstruct shale operators’ field development strategies and apply learnings to determine appropriate assumptions for future development plans.
• Oversee data organization and maintain internal databases covering geological formations, field development plans, and production forecasts.
• Collaborate with the Investments group by advising on cost, pricing, key assumptions and risk assessments.
• Interface with multidisciplinary teams including geoscientists, geoinformatics specialists, and finance professionals.

Qualifications:

• Minimum of a BE/BTech in Petroleum Engineering; an MS or PhD is a plus, especially if the research aligns with reserves estimation, petroleum economics, or production forecasting.
• Minimum of 5 years of hands-on petroleum engineering experience, with a focus on shale and tight-oil reservoir engineering, acquisition & divestment support, and reserves reporting across the US Lower 48.
• Proficiency with data visualization tools such as Spotfire.
• Demonstrated capability in the theory and application of Decline Curve Analysis.
• Familiarity with unconventional reservoirs and completion technologies.
• Working knowledge of basic finance concepts.

Ideal Skill Set:

• MS or PhD in Petroleum Engineering with a focus on fluid flow in porous media, decline curve analysis, or production forecasting.
• Demonstrable expertise in the evaluation and management of shale, tight oil, and tight gas reservoirs.
• Experience in drilling operations, well testing, and production optimization.
• Strong skills in Python (NumPy, Pandas, scikit-learn) and SQL are a significant plus.
• Advanced proficiency in data visualization tools such as Spotfire

Job Description:

Being part of our global petrotechnical team, this role will predominantly focus on the Oil & Gas vertical, offering insights, and expertise pertaining to the on-shore US territories. The position is an exceptional opportunity for individuals looking to build their career with an international firm and work in close collaboration with veterans from the top US shale operators.

Responsibilities:

• Undertake reservoir evaluations and interpretations to assess the viability and profitability of oil and gas extraction.
• Perform production analysis and forecasting across multiple onshore U.S. basins.
• Utilize proprietary software tools for predictive analyses regarding production levels.
• Deconstruct field development strategies of shale operators and use learnings to determine appropriate assumptions for future development plans
• Oversee data organization and maintain an internal database of the geological formations, field development plans and production forecasts.
• Work with the Investment Team, assisting in cost estimations, production forecasting, and risk assessments.
• Interface with multidisciplinary teams including geoscientists, reservoir engineers, and financial experts.

Qualifications:

• Minimum of a BS in Petroleum Engineering. MS or PhD is a plus, especially if research topic aligns with the domain of Estimation of Reserves, Petroleum Economics or Production Forecasting.
• 1-4 years of hands-on experience in Petroleum Engineering, with a focus on reservoir engineering or reserves reporting.
• Demonstrated ability in theory and application of Decline Curve Analysis.
• Familiarity with upstream Oil & Gas sector processes and technologies.
• Familiarty with unconventional reservoirs and completion technologies.
• Knowledge of basic finance concepts.
• Basic usage of data visualization tools such as Spotfire or Tableau.

Ideal Skill Set:

• MS or PhD in Petroleum Engineering with a focus on Fluid Flow in Porous Media, Decline Curve Analysis or Production Forecasting
• Demonstrable expertise in the evaluation and management of oil and gas reservoirs.
• Experience in drilling operations, well testing, and production optimization.
• Skills in Python (Numpy, Pandas, scikit-learn) and SQL are a significant plus.
• Proficiency in data visualization tools such as Spotfire or Tableau.
• Effective communication and presentation skills, capable of liaising with multidisciplinary teams.