Position Title: Staff Software Engineer

Skills Required

Python, AI/ML, Vertex AI, Azure ML, Lang Chain, 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 Gen AI 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 creative 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 Lang Chain, Lang Graph, 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, pg Vector, or similar vector databases.

Cloud AI: Deploys and manages machine learning and Gen AI 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, Gen AI, 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 e Commerce 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 & Gen AI: Large Language Models (LLMs) Prompt Engineering Lang Chain Lang Graph 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

Dev Ops & MLOps: Azure Dev Ops or Git Hub Actions CI/CD AI Model Deployment AI Monitoring

Databases: Postgre SQL Mongo DB 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 Big Query or Azure Synapse Terraform Helm Git Ops Real-time Event Streaming Distributed Systems Architecture

📌 Staff Engineer Software - Ai (Bengaluru)
🏢 Albertsons Companies India
📍 Bengaluru