About Albertsons Companies Inc. (ACI):
As a leading food and drug retailer in the United States, Albertsons Companies, Inc. operates over 2,200 stores across 35 states and the District of Columbia. Our well-known banners across the United States, including Albertsons, Safeway, Vons, Jewel-Osco and others, serve more than 36 million U.S customers each week.
We build and shape technology solutions that solve customers’ problems every day, making things easier for them when they shop with us online or in a store. We have made bold, strategic moves to migrate and modernize our core foundational capabilities, positioning ourselves as the first fully cloud-based grocery tech company in the industry.
Our success is built on a one-team approach, driven by the desire to understand and enhance the customer experience. By constantly pushing the boundaries of retail, we are transforming shopping into an experience that is easy, efficient, fun and engaging.
About Albertsons India Capability Center:
At Albertsons India Capability Center, we're not just pushing the boundaries of technology and retail innovation, we're cultivating a space where ideas flourish and careers thrive. Our workplace in India is a vital extension of the Albertsons Companies Inc. workforce and important to the next phase in the company’s technology journey to support millions of customers’ lives every day.
At the Albertsons India Capability Center, we are raising the bar to grow across Technology & Engineering, AI, Digital and other company functions, and transform a 165-year-old American retailer. At Albertsons India Capability Center, associates collaborate directly with international teams, enhancing decision-making processes and organizational agility through exciting and pivotal projects. Your work will make history and help millions of lives each day come together around the joys of food and inspire their well-being.
Position Title: Staff Software Engineer
Skills Required:
Python, AI/ML, Vertex AI, Azure ML, LangChain, RAG, Vector Databases
Experience Range:
9 - 12 years
Roles & responsibilities:
- Hands-on development of AI-powered applications using Python, conducting code reviews and continuously improving application quality, scalability, and reliability.
- Performs advanced development, support, and implementation of enterprise AI solutions using specialized business and domain expertise.
- Partners with Architects to translate enterprise AI and GenAI strategies into detailed solution designs and implementation plans.
- Leads large AI and machine learning initiatives with limited or no oversight.
- Evaluates AI, Machine Learning, and Generative AI industry trends and recommends technologies and approaches that improve business outcomes.
- Proposes and champions innovative AI solutions, architectures, and engineering practices that enhance operational efficiency and customer experience.
- Sets standards to deliver high-quality AI products and services while maintaining responsible AI principles, governance, and security.
- AI Engineering: Designs and develops enterprise AI applications using Python, leveraging Large Language Models (LLMs), prompt engineering, and AI orchestration frameworks.
- AI Engineering: Designs and implements Retrieval Augmented Generation (RAG) architectures, embedding pipelines, semantic search solutions, and enterprise knowledge retrieval platforms.
- AI Engineering: Builds production-grade AI agents using LangChain, LangGraph, ADK, or similar frameworks including tool calling, memory management, orchestration, and human-in-the-loop workflows.
- Data & AI: Designs and implements vector search solutions using Azure AI Search, Vertex AI Vector Search, Pinecone, Weaviate, pgVector, or similar vector databases.
- Cloud AI: Deploys and manages machine learning and GenAI workloads using Vertex AI or Azure Machine Learning platforms, including training, inference, monitoring, and model lifecycle management.
- AI Integration: Designs and implements AI-driven integrations with enterprise platforms using REST APIs, Kafka, Apache Camel, event-driven architectures, and microservices.
- Computer Vision & Multimodal AI: Develops solutions involving image, video, OCR, document intelligence, and multimodal AI capabilities for business use cases.
- AI Governance: Implements responsible AI controls, model evaluation, tracing, observability, prompt security, guardrails, and performance monitoring.
- Quality Engineering: Defines testing and validation strategies for AI applications, including model evaluation, prompt testing, integration testing, and automated testing frameworks.
- Performance Engineering: Monitors and optimizes AI applications for response quality, latency, throughput, scalability, model cost, and resource utilization.
- Production Operations: Ensures AI services run reliably in production environments using an SRE mindset including observability, monitoring, tracing, incident management, and operational readiness.
- Mentors engineers on AI, ML, GenAI, Cloud AI platforms, architecture patterns, and engineering best practices.
Experience Required:
- 9+ years of software engineering experience developing enterprise applications.
- 4+ years of experience leading engineering teams and delivering large-scale technology initiatives.
- 5+ years of programming experience using Python and developing enterprise-grade applications.
- 3+ years of experience designing and implementing AI/ML or Generative AI solutions.
- Hands-on experience with Large Language Models (LLMs), prompt engineering, and AI-powered application development.
- Experience designing and implementing Retrieval Augmented Generation (RAG) solutions.
- Experience working with vector databases and semantic search technologies.
- Experience deploying AI/ML models using Vertex AI or Azure Machine Learning platforms.
- Experience developing cloud-native applications on Azure or GCP.
- Experience developing REST APIs, microservices, and event-driven architectures.
- Experience integrating enterprise systems using Kafka, Apache Camel, APIs, and messaging technologies.
- Experience implementing MLOps, CI/CD pipelines, model deployment, monitoring, and governance processes.
- Broad expertise with software development lifecycle methodologies including Agile practices.
- Experience analyzing and optimizing AI application performance, scalability, and operational cost.
- Experience implementing enterprise-grade security, compliance, and responsible AI practices.
Competencies:
- Compassionate and kind, showing courtesy, dignity, and respect. They show sincere interest and empathy for all others
- Foster innovation through creativity to get a workable solution. Use analytical thinking through issues using logic and reason
- Show integrity in what is done and how it is done - without sacrificing personal/business ethics
- Embrace an inclusion-focused mindset, seeking input from others on their work and encouraging the open expression of diverse ideas and opinions
- Team-oriented, positively contributing to team morale and willing to help
- Learning-Focused, finding ways to improvise in their field and use positive constructive feedback to grow personally and professionally
- Think strategically and proactively anticipate future problems, needs or changes in the work
- Delighting our customers and maintaining customer relationships are top priority and they work to always deliver solutions through this lens
- Retail Industry and eCommerce Experience is a must
- Extensive experience in mentoring development teams and delivering large scale application
- Strong expertise in ensuring the application is designed and can run in production environments with an SRE (Site Reliability Engineering) mindset
- Proficient in design patterns and architectural skills, with a proven track record of delivering large-scale initiatives while managing multiple parallel projects effectively
Mandatory Skills Required:
Programming Languages:
- Python
- SQL
AI & GenAI:
- Large Language Models (LLMs)
- Prompt Engineering
- LangChain
- LangGraph
- RAG Architecture
- Agentic AI Frameworks
Cloud AI Platforms:
- Google Vertex AI and/or Azure Machine Learning
Vector Databases:
- Azure AI Search
- Vertex AI Vector Search
AI Development:
- Embedding Models
- Semantic Search
- AI Agent Development
- Function Calling
- Knowledge Graphs
- MCP (Model Context Protocol)
- Azure AI Services
- Vertex AI Agent Builder
- Google Agent Development Kit (ADK)
Cloud Technologies:
- Azure or GCP
- Docker
- Kubernetes
Integration:
- REST APIs
- Apache Kafka
- Apache Camel
- Event-Driven Architecture
- FAST API
DevOps & MLOps:
- Azure DevOps or GitHub Actions
- CI/CD
- AI Model Deployment
- AI Monitoring
Databases:
- PostgreSQL
- MongoDB
- Cassandra
- Vector Databases
Domain:
- Supply Chain
Good to have Skills:
- Computer Vision & Vision AI
- OCR & Document Intelligence
- MLOps
- AI Evaluation Frameworks
- AI Security & Governance
- Responsible AI
- Prompt Security
- Feature Stores
- BigQuery or Azure Synapse
- Terraform
- Helm
- GitOps
- Real-time Event Streaming
- Distributed Systems Architecture