Lead Engineer - Ad Tech

About us: As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up . Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.

Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.

Team Overview:   Roundel is Target’s entry into the media business with an impact of $1B+; an advertising sell-side business built on the principles of first-party, people-based data, brand-safe content environments and proof that our marketing programs drive business results for our clients.  

We are here to drive business growth for our clients and redefine “value” in the industry by solving core industry challenges rather than simply replicating existing industry methods of operation. Roundel is a key growth initiative for Target and aims to lead the industry toward a better way of operating within the media marketplace.  

Target Tech is on a mission to offer the systems,   tools   and support that our clients, guests and team members need and deserve. We drive industry-leading   technologies in support of every angle of the business and help ensure that Target   operates   smoothly,   securely   and reliably from the inside out.  

As part of this evolution,   we are building intelligent platforms   for retail media space like ad decisioning, bidding, ad explanations   etc.    that combine traditional software engineering with Large Language Models, retrieval systems, knowledge   graphs   and agentic architectures to solve complex business and engineering problems at scale.  

Role Overview:  

As a   Lead Engineer (Ad Tech & Applied AI) , you will provide technical leadership across backend platforms and emerging AI-powered capabilities.  

You will collaborate with cross-functional teams to help define the technology strategy for Ad Tech platforms, including DSP, SSP and Ad Servers, supporting self-service advertising needs. You will assess build-versus-buy decisions for new capabilities through POCs and prototypes while considering long-term architecture, scalability,   reliability   and operational trade-offs.  

A key part of this role will be designing and buildin g   production-grade applications powered by Large Language Models and agentic systems   from experimentation through production operation and continuous evaluation . We are looking for engineers who have moved beyond conversational AI prototypes and have experience engineering LLM-powered systems that   operate   reliably within   real business   workflows.  

You will design architectures that combine deterministic software components with probabilistic AI capabilities, making deliberate decisions about where traditional code, rules and workflow engines should be used versus where LLM-driven reasoning and autonomous agents provide value.  

You will lead engineering efforts to meet functional and non-functional requirements and   assist   teams in solving complex business challenges through scalable technical solutions.  

You will work closely with engineering managers to build high-performing engineering teams and provide technical leadership, architecture guidance,   coaching   and mentoring. You will also   participate   in the   selection   of technical talent and contribute actively to Target’s broader technical community.  

About you:  

You have   8+ years of software development experience , with experience designing,   building   and   operating   complex distributed systems through at least one complete implementation lifecycle.  

You have strong backend engineering fundamentals and are comfortable designing scalable APIs, microservices, asynchronous systems and data-intensive applications.  

You are fluent in   Java / Spring and microservices architecture , with experience building   highly available   production systems.  

You have experience working with databases including   RDBMS and NoSQL technologies such as Cassandra and   MongoDB , and   understand data   modeling   and storage trade-offs.  

You have experience building distributed event-driven architectures using technologies such as   Kafka .  

You understand Ad Tech business fundamentals and how technology supports business   objectives, and   can translate business vision into technical strategy while understanding architectural and financial trade-offs.  

Experience building or integrating   DSP, SSP or Ad Server technology platforms   in support of self-service advertising is preferred.  

Applied AI & LLM Engineering  

You have hands-on experience   designing,   building   and   operating   production applications using LLMs , beyond chat interfaces, prompt   experimentation   and proof-of-concept applications.  

You have designed and optimized production-grade   RAG systems , with strong understanding of   data ingestion and chunking, retrieval and ranking, context and grounding, hybrid retrieval, and evaluation .  

You have experience with   knowledge graphs and graph-based retrieval , and understand when to use vector search, Graph RAG, structured queries, traditional   search   or hybrid approaches based on the problem and data.  

You understand the engineering trade-offs of production LLM systems, including   quality, latency, cost, reliability, observability,   security   and failure handling , and can systematically improve retrieval and overall system performance rather than relying primarily on prompt engineering.  

Agentic Systems  

You have designed or built   agentic applications or orchestration frameworks   where LLM-powered components interact with tools, APIs, retrieval   systems   and other agents to   accomplish   multi-step tasks.  

You understand concepts such as:  

Tool/function calling  

Agent planning and execution  

Workflow and state management  

Multi-agent orchestration  

Agent memory and context management  

Routing and delegation  

Human-in-the-loop workflows  

Guardrails and policy enforcement  

Retry, timeout and fallback strategies  

Agent observability and traceability  

Evaluation of agent   behavior   and task completion  

You understand the distinction between   deterministic and non-deterministic execution paths   and can design systems that deliberately combine both.  

You know when a business workflow should remain deterministic and testable using conventional software and when probabilistic reasoning using an LLM or agent is   appropriate .  

You design AI systems assuming that model outputs can be incorrect or unpredictable and therefore incorporate   appropriate   validation , constraints, structured outputs, fallbacks, idempotency, observability and human intervention   where   required .  

AI Quality & Evaluation  

You understand that production AI systems require rigorous   quality and evaluation practices   beyond model selection and prompting.  

You have experience   establishing   offline and online evaluation strategies   for LLM-powered systems, covering retrieval and response quality,   factual grounding , task completion, reliability,   latency   and cost.  

You can build   evaluation harnesses and regression tests   with representative datasets,   metrics   and quality thresholds, and integrate them into   CI/CD as deployment and quality gates .  

You can use evaluation,   observability   and tracing to diagnose quality issues across   data, retrieval, context, prompts,   models   and orchestration , and drive systematic improvements.  

Engineering Leadership  

You can translate ambiguous business problems into clear technical architectures and incrementally deliver solutions from experimentation through production.  

You make architecture decisions based on measurable trade-offs rather than technology trends and are comfortable challenging unnecessary complexity.  

You can lead   POCs and technical experiments   while clearly distinguishing between what   demonstrates   feasibility and what is   required   to   operate   the capability reliably at enterprise scale.  

You have proven technical leadership capabilities and the ability to influence engineers, product   leaders   and cross-functional stakeholders.  

You enjoy mentoring engineers and raising the technical capabilities of the broader engineering team.  

You collaborate effectively with Product and domain experts and can communicate complex architecture decisions to both technical and non-technical stakeholders.  

You stay current with evolving engineering and AI technologies through formal training and self-directed learning, while applying   new technologies   pragmatically.  

You have experience working within   CI/CD and DevOps environments   and understand production engineering practices including monitoring, observability, resilience,   security   and operational readiness.  

Useful Links: Life at Target: https://india.target.com/

Benefits: https://india.target.com/life-at-target/workplace/benefits

Culture: https://india.target.com/life-at-target/belonging