Sr Engineer

Target is hiring a Sr Engineer in Bengaluru, India. Level rates it ; you can apply on Target.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include RAG and AI agents.
Level classifies it as a senior role.
Level lists 1,600+ other open roles at Target.
The role was posted within the past two weeks.

AI in this role

ragai-agents

About us:
Target is an iconic brand, a Fortune 50 company and one of America’s leading retailers.

Target as a tech company? Absolutely. We’re the behind-the-scenes powerhouse that fuels Target’s passion and commitment to cutting-edge innovation. We anchor every facet of one of the world’s best-loved retailers with a strong technology framework that relies on the latest tools and technologies—and the brightest people—to deliver incredible value to guests online and in stores. Target Technology Services is on a mission to offer the systems, tools and support that guests and team members need and deserve. Our high-performing teams balance independence with collaboration, and we pride ourselves on being versatile, agile and creative. 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.

Role Overview
We are looking for a Senior Engineer to build reusable platform capabilities for PIQ, focusing on context building, graph-based retrieval, agent harnesses, and statistical modeling. The role combines software engineering with the development of frameworks that support intelligent applications and AI agents.

Key Responsibilities

Harness Building & Scaffolding: Develop reusable agent harnesses, frameworks, and project scaffolding for tool integration, workflow execution, testing, and evaluation.
Context Building: Build capabilities to gather, structure, enrich, and manage context from diverse data sources for applications and AI agents.
Graph Creation & Graph RAG: Develop graph models and graph-based retrieval-augmented generation workflows to connect information and retrieve relevant context.
Statistical Modeling & Simulation: Develop and validate models that represent variability, estimate outcomes, and support scenario simulation.
Platform Engineering: Design scalable APIs and services, own technical delivery, and maintain engineering quality through testing, documentation, and mentoring.

Required Qualifications

5+ years of software engineering experience, with proficiency in Python, Java, or a similar programming language.
Strong foundations in data structures, algorithms, data modeling, SQL, and API development.
Experience building production-grade services and reusable frameworks, with working knowledge of statistics and modeling.

Preferred Experience
Exposure to AI agent frameworks, context engineering, knowledge graphs, RAG or Graph RAG, and simulation. Familiarity with cloud platforms and enterprise data systems is a plus

How we rate this

Sr Engineer at Target rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Sr Engineer is an open job at Target.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Bangalore,India.
The job was posted on October 14, 2026.
Seniority: senior.
Applications are handled by Target. Apply on Target

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agents

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: RAG and AI agents. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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