Senior Engineer Software - Agentic AI [T500-29886]
About Albertsons:
As a leading food and drug retailer in the United States, Albertsons Companies, Inc. (ACI) operates over 2,200 stores across 34 states and the District of Columbia. Our well-known global banners, including Albertsons, Safeway, Vons, Jewel-Osco and others.
Our success is built upon a united team approach, driven by the desire to understand and enhance the customer experience. This customer-centric focus not only inspires innovation but has also led to remarkable achievements across our digital platforms and omnichannel strategies. By constantly pushing the boundaries of retail, we have transformed shopping into an experience that is not just easy and efficient, but also fun and engaging.
Over the past year, we have taken bold, strategic steps to migrate and modernize our enterprise data hub on Google Cloud, revolutionizing our data capabilities, thus becoming the first fully cloud-based grocery tech company.
About Tech Hub in India:
Albertsons Companies India (ACI India) is part of Albertsons Companies Inc. global workforce. As Albertsons' first significant strategic investment in India, it serves as a collaborative hub, supporting Albertsons in driving innovation and efficiency across Technology, Digital, and other key business functions. The associates at the India GCC will play a pivotal role in enhancing the company's digital transformation, customer engagement, and operational excellence, contributing significantly to Albertsons Companies' mission to earn Customers for Life.
We are excited to announce an opening for Senior Engineer Software at ACI. Please find below the details of the role and its responsibilities.
Position Title: Senior Engineer Software
We are looking for a Senior Software Engineer to help build intelligent shopping experiences powered by generative AI. You will design and deliver AI-powered agents that help customers discover products, compare options, answer shopping questions, create personalized recommendations, and complete shopping journeys with confidence.
This role combines strong software engineering fundamentals with modern AI application development. Success is measured by the quality, trustworthiness, reliability, and business impact of customer experiences—not simply by the volume of code produced.
Roles & responsibilities:
- Design and build scalable services that power conversational and agentic shopping experiences.
- Develop intelligent workflows that combine LLMs with enterprise data, APIs, business rules, search, recommendations, and commerce systems.
- Translate ambiguous customer problems into intuitive AI-powered product experiences.
- Build reliable integrations with product catalogs, pricing, promotions, inventory, fulfillment, loyalty, customer profile, and transaction services.
- Design robust prompt orchestration, retrieval pipelines, tool calling, and context management strategies.
- Implement evaluation frameworks to measure accuracy, grounding, relevance, customer satisfaction, latency, safety, and business outcomes.
- Ensure AI responses are trustworthy, explainable where appropriate, and aligned with business policies and customer expectations.
- Build resilient systems that gracefully handle uncertainty, incomplete information, failures, and model limitations.
- Design observability into AI applications, including telemetry, tracing, prompt analytics, evaluation metrics, and production monitoring.
- Partner with product managers, UX designers, conversational designers, and AI specialists to iterate rapidly on customer experiences.
- Participate in architecture and code reviews while mentoring engineers on modern AI engineering practices.
- Improve engineering productivity through automation and responsible use of AI-assisted development tools.
AI-Native Engineering Expectations:
Senior engineers are expected to leverage AI as an engineering accelerator while maintaining complete ownership of technical quality and customer outcomes.
You should be able to:
- Build production-grade applications using foundation models, retrieval-augmented generation (RAG), tool use, and agentic workflows.
- Select appropriate models and architectures based on latency, quality, cost, reliability, and privacy requirements.
- Design prompts, structured outputs, and orchestration strategies that produce predictable and maintainable behavior.
- Validate AI-generated responses using evaluation frameworks, automated testing, and human feedback.
- Recognize and mitigate hallucinations, prompt injection, unsafe outputs, bias, and other AI-specific failure modes.
- Design guardrails that ensure customer interactions are safe, compliant, and aligned with business policies.
- Use AI-assisted development tools to accelerate implementation while critically reviewing and validating all generated code.
- Protect customer and enterprise data by applying appropriate privacy, security, and governance practices when building AI-powered applications.
Qualification and Competencies:
- 6 – 9 years of overall experience
- Strong software engineering fundamentals, including object-oriented design, distributed systems, APIs, testing, and cloud-native development.
- Experience designing and operating production services at scale.
- Experience building customer-facing applications with high standards for availability, performance, and usability.
- Experience integrating LLMs or other generative AI capabilities into production software.
- Experience with retrieval systems, semantic search, vector databases, or knowledge grounding.
- Strong understanding of API design, event-driven architectures, and microservices.
- Experience with experimentation, A/B testing, feature flags, and data-driven product development.
- Strong debugging and root-cause analysis skills across distributed systems.
- Excellent communication and collaboration skills.
Preferred Qualifications:
- Experience building conversational AI, copilots, assistants, or autonomous agents.
- Experience in e-commerce, retail, digital marketplaces, or shopping experiences.
- Familiarity with recommendation systems, search, personalization, pricing, or merchandising.
- Experience implementing AI evaluation frameworks and prompt management workflows.
- Experience with observability for AI applications, including prompt tracing, quality metrics, and model monitoring.
- Experience designing systems that balance AI capabilities with deterministic business logic.