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.
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 building 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.
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.
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:
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.
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.
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
