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Senior Software Engineer at Epsilon

NEW
Location
Bengaluru, Karnataka, India
Job type
Full time
Posted 1 day ago
Description

About the job

Overview


About the Role:


We are looking for a Senior AI Engineer to join our AI Center of Excellence team at Epsilon, working at the heart of enterprise-grade Conversational, Agentic, and AI Platforms and applications. This role is for someone who brings a strong software engineering backbone, a data-oriented mindset, and deep hands-on expertise in Generative AI, RAG, and Agentic AI systems and is ready to help shape the future of intelligent, enterprise systems at scale.


You will be building and scaling AI-powered applications and agents that serve thousands of associates and clients across Epsilon and Publicis Groupe, integrating with enterprise systems. You will own and operate across the full lifecycle - from ideation, experimentation and prototyping to production hardening, evaluation, and operational governance.


Responsibilities


What You'll Do:


Core Engineering & Architecture


  • Design, develop, and ship production-grade AI applications - including conversational Assistants, RAG pipelines, and multi-agent systems.
  • Architect scalable, secure, and cost-efficient backend services using Python, Node.js, and cloud-native patterns (AWS / Azure/ GCP).
  • Build and maintain API services (RESTful, streaming) that integrate AI capabilities with enterprise systems.
  • Write clean, testable, well-documented code with CI/CD best practices; champion engineering rigor in an AI-first team.


Generative AI & LLM Systems


  • Build and optimize LLM-powered features - including prompt engineering, structured output design, tool/function calling, and context management (multi-turn conversations, session handling).
  • Design and implement evaluation frameworks (groundedness scoring, regression testing, quality benchmarking) for AI outputs - ensuring trust, accuracy, and continuous improvement.
  • Stay hands-on with LLM APIs (Azure OpenAI, AWS Bedrock, Anthropic, open-source models) and make informed decisions on model selection, cost-latency tradeoffs, and fine-tuning vs. prompting strategies.


Retrieval-Augmented Generation (RAG)


  • Design and build enterprise RAG pipelines - including embedding selection, chunking strategies, metadata enrichment, hybrid retrieval, re-ranking, and citation/traceability.
  • Integrate and manage vector databases for scalable knowledge retrieval across heterogeneous enterprise data sources.
  • Continuously improve retrieval quality by building golden test sets, measuring relevance, and implementing feedback loops.
  • Work with Multimodal retrieval based on unstructured content.


Agentic AI & Orchestration


  • Design and implement agentic workflows - autonomous and semi-autonomous AI agents that can reason, plan, use tools, and execute multi-step business workflows with human-in-the-loop checkpoints.
  • Build multi-agent orchestration frameworks using tools like AWS Bedrock, Agentcore, Cursor and other state-of-the-art open-source frameworks - enabling collaborative agent systems for complex enterprise scenarios.
  • Develop reusable tool integrations that agents can invoke autonomously, with proper guardrails and safety controls.


Data & Analytics Mindset


  • Work with structured and unstructured enterprise data — cleaning, transforming, and preparing data for AI consumption.
  • Apply data science fundamentals (EDA, statistical analysis, anomaly detection) to diagnose issues, validate model behavior, and derive actionable insights from AI system telemetry.
  • Collaborate with data engineering teams to ensure data pipelines are reliable, timely, and aligned with AI feature needs.


Governance, Safety & Ops


  • Implement Responsible AI practices - including guardrails for hallucination handling, PII protection, restricted topic filtering, and compliance with enterprise security standards.
  • Build and operate LLMOps / MLOps pipelines - model deployment, monitoring, logging, tracing, cost tracking, and lifecycle management.
  • Contribute to SoPs, governance documentation, and operational runbooks for AI systems deployed across teams.


Qualifications


Must-Have Skills & Experience:


  • Experience: 5–8+ years in software engineering, with at least 2+ years hands-on in Generative AI / LLM-based systems
  • Software Engineering: Strong proficiency in Python; experience with backend frameworks (FastAPI, Flask, Express/Node.js); clean API design, version control (Git), testing, and CI/CD
  • Generative AI: Hands-on experience with LLM APIs (Azure OpenAI, AWS Bedrock, Anthropic, Google Gemini); prompt engineering, structured outputs, tool/function calling
  • RAG: Proven experience building RAG pipelines - embedding models, chunking, retrieval logic, vector database, re-ranking, and grounding
  • Agentic AI: Experience designing agent-based architectures - tool use, planning, multi-step workflows; familiarity with AWS Bedrock, Azure AI Foundry, or equivalent frameworks
  • Data Fundamentals: Solid understanding of data wrangling, SQL, EDA, and basic ML concepts; ability to work with structured/unstructured data at scale
  • DataBricks: Designs, builds, and manages scalable data pipelines and AI solutions within the Databricks Lakehouse Platform
  • Cloud: Experience with AWS or Azure - deploying containerized services, serverless functions, and working with cloud AI/ML services
  • System Design: Ability to design distributed, scalable AI systems with clear tradeoffs on cost, latency, and reliability


Good-to-Have / Forward-Looking Skills


  • Multi-Agent Systems & A2A Protocols - experience with agent-to-agent communication patterns, Model Context Protocol (MCP), or similar emerging standards.
  • Fine-Tuning & Model Adaptation - experience fine-tuning LLMs or adapter-based methods (LoRA, QLoRA) for domain-specific use cases.
  • AI Evaluation & Benchmarking - experience building evaluation harnesses, automated grading, and regression testing for LLM outputs.
  • Microsoft Ecosystem - familiarity with M365 Copilot, Copilot Studio, Bot Framework, Teams integrations, Adaptive Cards.
  • Observability & Tracing - experience with AI-specific observability for debugging and monitoring AI systems in production.
  • NLP & Classical ML - deeper grounding in NLP (named entity recognition, text classification, sentiment analysis) and classical ML (scikit-learn, XGBoost).
  • Knowledge Graphs & Hybrid Search - experience combining graph-based retrieval with vector search for richer contextual grounding.
  • Edge / Cost Optimization - techniques for reducing inference cost, including model distillation, quantization, caching, and batching strategies.
  • Security & Compliance - awareness of data privacy regulations, secure API design, and AI red-teaming / adversarial testing.


What Sets You Apart


  • You think like a software engineer first - you care about clean code, testable systems, and operational excellence - and you apply that rigor to AI systems.
  • You have a builder's mindset - you're not just consuming APIs; you're designing platforms, building reusable components, and thinking about how your work scales to 50+ teams.
  • You bring data intuition - you can EDA your way through a problem, validate model behavior with data, and explain tradeoffs with metrics.
  • You're curious and forward-looking - you track the evolving landscape of AI agents, evaluation, and orchestration and bring those ideas to the team.
  • You thrive in a fast-paced, collaborative environment where you work closely with product, operations, and leadership to deliver measurable impact.


Education


Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent practical experience).


Additional Information


Epsilon is a global data, technology and services company that powers the marketing and advertising ecosystem. For decades, we’ve provided marketers from the world’s leading brands the data, technology and services they need to engage consumers with 1 View, 1 Vision and 1 Voice. 1 View of their universe of potential buyers. 1 Vision for engaging each individual. And 1 Voice to harmonize engagement across paid, owned and earned channels.


Epsilon’s comprehensive portfolio of capabilities across our suite of digital media, messaging and loyalty solutions bridge the divide between marketing and advertising technology. We process 400+ billion consumer actions each day using advanced AI and hold many patents of proprietary technology, including real-time modeling languages and consumer privacy advancements. Thanks to the work of every employee, Epsilon has been consistently recognized as industry-leading by Forrester, Adweek and the MRC. Epsilon is a global company with more than 9,000 employees around the world.


Our pillars aren't just words. They're how we show up every day.


  • People centricity: We focus on employee well-being in an environment where colleagues truly care about each other.
  • Collaboration: We work together, support one another, and collectively achieve goals.
  • Growth: There are endless opportunities for growth through learning, development and career advancement.
  • Innovation: We drive progress through cutting-edge solutions and forward-thinking approaches.
  • Flexibility: We’ve created a balance between work and personal life, and we encourage adaptability to solve problems creatively.


Our values guide us to create value for our clients, our people and consumers.


  • Act with integrity
  • Work together to win together
  • Innovate with purpose
  • Respect all voices
  • Empower with accountability


These pillars and values are our foundation—shaping our culture, guiding our decisions, and uniting us in common purpose.


Epsilon is an Equal Opportunity Employer.


Epsilon is committed to promoting diversity, inclusion, and equal employment opportunities by using reasonable efforts to attract, recruit, engage and retain qualified individuals of all ethnicities and backgrounds, including, but not limited to, women, people of color, LGBTQ individuals, people with disabilities and any other underrepresented groups, traits or characteristics.

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Frequently Asked Questions

What is the Senior Software Engineer at Epsilon role?
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Why Work at Epsilon?

A Senior Software Engineer at Epsilon can take on work that combines hands-on software development with technical judgment and collaboration. This full-time, senior-level opportunity is based in Bengaluru, Karnataka, India. For experienced engineers looking to contribute beyond individual tasks, a senior role can offer the chance to influence how software is designed, built, tested, and maintained.

Senior engineers often help teams turn product or business requirements into dependable technical solutions. That can involve evaluating different approaches, identifying risks early, and helping colleagues make decisions that support both current needs and future development. The exact projects, tools, and responsibilities for this Epsilon role should be confirmed in the official job listing and during the hiring process, since they are not specified in the job details available here.

Working at a company with engineering teams may also provide opportunities to collaborate across disciplines. Depending on the team, that collaboration could include product, design, quality assurance, data, or other engineering groups. Senior contributors can bring value by explaining technical trade-offs clearly, aligning implementation with requirements, and helping the team deliver work in manageable stages.

Candidates considering this role may want to learn more about Epsilon’s engineering organization, the product or platform team hiring, and how success is measured for senior engineers. The LinkedIn job listing is the best source for current application information, role requirements, and any details not included in the available posting summary.

What’s It Like to Work at Epsilon?

The experience of working at Epsilon can vary by team, project, and manager. For this Bengaluru-based engineering position, candidates should use conversations with the hiring team to understand the day-to-day environment rather than assume that every Epsilon team works in the same way.

A useful way to evaluate a potential workplace is to ask how engineering decisions are made. For example, candidates can ask how teams balance delivery timelines with reliability, maintainability, and technical debt. It is also worth learning how engineers share knowledge, review code, and coordinate when projects involve multiple teams. These details can help you understand whether the team’s working practices fit your preferences.

As a senior engineer, you may be expected to contribute both independently and collaboratively. Senior-level work commonly involves taking ownership of complex problems, communicating progress and risks, and helping teammates navigate technical questions. The scope of that responsibility at Epsilon should be clarified during interviews, especially if you want to understand the balance between coding, design discussions, mentoring, and project coordination.

Before applying, consider asking about the team’s current priorities, development workflow, and expectations for the first few months. You can also ask how the organization supports professional growth and how performance is evaluated. These questions help you build a realistic picture of the role and decide whether the opportunity aligns with your career goals.

What’s It Like to Work as a Senior Software Engineer at Epsilon?

The Senior Software Engineer at Epsilon role is listed as a full-time, senior-level position in Bengaluru. The available job details do not specify a technology stack, minimum years of experience, salary range, or a full list of responsibilities. As a result, candidates should confirm those points directly through the official listing or with the recruiter.

In many senior software engineering roles, the work extends beyond writing code. A senior engineer may be asked to understand a problem thoroughly, identify suitable implementation options, and explain the advantages and limitations of each. They may also help divide large initiatives into deliverable pieces, anticipate operational concerns, and ensure that engineering decisions are clear to others on the team.

Depending on the team’s needs, the role could include activities such as:

  • Designing or improving software components and services.
  • Reviewing code and giving constructive technical feedback.
  • Investigating defects, performance issues, or reliability concerns.
  • Collaborating with colleagues to clarify requirements and priorities.
  • Helping establish or improve engineering practices.
  • Supporting less experienced engineers through knowledge-sharing.
  • Communicating technical risks and progress to relevant stakeholders.

These are common areas of responsibility for senior software engineers, not a confirmed list of Epsilon-specific duties. Use the interview process to learn what the role actually owns and how much time is devoted to implementation versus technical leadership.

To prepare, think of examples where you solved a difficult engineering problem, improved an existing system, or helped a team make a sound technical decision. Strong examples explain the context, your contribution, the reasoning behind your approach, and the outcome. If a project involved trade-offs—such as speed versus maintainability—describe how you assessed those trade-offs and communicated them.

Senior Software Engineer Interview Questions at Epsilon

The questions below are practice prompts, not verified questions from Epsilon’s interview process. They can help you prepare for discussions commonly associated with senior software engineering roles. The actual interview format and topics may differ.

Technical and system design questions

  1. How would you design a service to handle a significant increase in traffic?
  2. How do you decide whether a component should be split into separate services or remain part of a larger application?
  3. What factors do you consider when designing an API that needs to remain maintainable over time?
  4. How would you investigate a production issue that is difficult to reproduce?
  5. Describe how you would improve the performance of a system without compromising its reliability.
  6. How do you approach testing when working with legacy code?
  7. What makes a code review useful, and how do you respond to disagreement during one?
  8. How do you evaluate a new tool, library, or architectural approach before recommending it?

Experience and collaboration questions

  1. Tell us about a technically challenging project you delivered. What was your role?
  2. Describe a time you had to make a decision with incomplete information.
  3. How have you helped a team address technical debt?
  4. Share an example of a disagreement about a technical direction. How did you work toward a resolution?
  5. How do you communicate project risks to people with different technical backgrounds?
  6. Tell us about a time you supported or mentored another engineer.
  7. What do you do when a delivery deadline conflicts with concerns about quality or maintainability?

When answering, use specific examples rather than broad claims. Explain what you personally did, what alternatives you considered, and what you learned. If the outcome was not ideal, describe how you responded and what you would change next time. For system design prompts, make your assumptions explicit, ask clarifying questions, and explain how your design addresses reliability, scale, security, and operational needs.

Senior Software Engineer Interview Preparation at Epsilon

Start by reviewing the official job listing carefully. The available details identify the position as a full-time Senior Software Engineer role in Bengaluru, but do not provide a confirmed technology stack or detailed requirements. Note any new information in the live listing and prepare questions about areas that remain unclear, such as the team’s technical environment, product area, and expectations for the position.

Next, prepare a concise summary of your experience. Be ready to explain the kinds of systems you have worked on, the problems you have solved, and the level of ownership you have had. Since this is a senior-level opportunity, focus on examples that show sound judgment, accountability, and an ability to work effectively with others—not only familiarity with programming languages or frameworks.

Review core technical topics that match your own experience and the requirements listed in the official posting. Preparation may include practicing system design, discussing API and data modeling choices, reviewing testing strategies, and revisiting debugging or performance investigations. Avoid guessing which specific technologies Epsilon will use; instead, be prepared to explain how you approach unfamiliar tools and how you make technical decisions.

Prepare several examples using a clear structure:

  • Situation: What was the project or problem?
  • Task: What were you responsible for?
  • Action: What steps did you take, and why?
  • Result: What changed, and how did you measure the outcome?

Choose examples that demonstrate different strengths—for instance, technical problem-solving, collaboration, handling uncertainty, improving quality, and supporting teammates. Where appropriate, include measurable outcomes, but explain the context behind the numbers so they are meaningful.

Finally, prepare thoughtful questions for the interviewer. You might ask what the team expects the new hire to accomplish in the first few months, how technical decisions are reviewed, what kinds of challenges the team is currently addressing, and how success in the role is evaluated. These questions can help you assess the opportunity while showing that you are considering the responsibilities carefully.

Senior Software Engineer Interview Tips at Epsilon

For the Senior Software Engineer at Epsilon interview, communicate your reasoning as clearly as your final answer. In technical discussions, explain assumptions, ask clarifying questions, and outline your approach before moving into implementation details. If there are several reasonable solutions, compare them and explain why you would choose one for the situation described.

For system design conversations, avoid jumping straight to a diagram or a preferred architecture. First establish the problem’s requirements, expected usage, constraints, and important failure cases. Then discuss the main components and how they interact. A strong answer considers more than the happy path: think about observability, testing, security, failure recovery, and future changes where relevant.

In behavioral interviews, be precise about your own contribution. Senior engineers often work as part of a group, so acknowledge the team’s role while making your individual decisions and actions clear. Show how you handled feedback, communicated trade-offs, and adapted when circumstances changed.

You should also use the interview to evaluate the position. Since details such as compensation, technology stack, and specific responsibilities are not included in the available job information, ask the recruiter or hiring team for clarification. Confirm the role’s scope, location expectations, interview stages, and any other factors that matter to your decision. For application details and the latest requirements, refer to the official Epsilon job listing on LinkedIn.