{"id":68821,"url":"https://alion.io/job/accrete-ai-staff-engineer-application-development","title":"AI Staff Engineer- Application Development","company":{"id":27720,"name":"Accrete","domain":"accrete.ai","url":"https://alion.io/company/accrete","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":80000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":10},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache HTTP Server","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"Cassandra","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Dagster","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"DynamoDB","optional":false},{"name":"ElasticSearch","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google ADK","optional":false},{"name":"Google BigQuery","optional":false},{"name":"GraphQL","optional":false},{"name":"gRPC","optional":false},{"name":"Hadoop","optional":false},{"name":"HBase","optional":false},{"name":"JUnit","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"Memcached","optional":false},{"name":"Memgraph","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"MySQL","optional":false},{"name":"Neo4j","optional":false},{"name":"NumPy","optional":false},{"name":"OpenSearch","optional":false},{"name":"Oracle","optional":false},{"name":"Pandas","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Selenium","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"WebSockets","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-08-19T09:15:46Z","employer_posted_date":"2026-08-19","last_verified_at":"2026-10-16T18:40:45Z","board_verified":true,"closed_at":null,"days_open":58,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":58},"description":"Company Overview:\nJoin our team at Accrete (https://www.accrete.ai), a product-focused AI company building intelligence-driven platforms that help organizations understand, assess, and act on complex information at scale using GenAI and agentic approaches. We focus on solving real enterprise problems by combining applied AI, strong engineering, and thoughtful system design to deliver measurable business outcomes across industries.\nPosition Overview:\nWe are seeking a Staff Engineer who is excited about building the next phase of our platform with an agent-first, AI-native approach, grounded in clean code and strong architectural thinking. This role goes beyond traditional backend or data engineering. You will design and build systems where LLMs can reason, plan, and act, working alongside well-structured, deterministic services and workflows. The goal is simple and demanding at the same time: ship systems that work reliably in production, scale with real usage, and solve real customer problems.\nThis is a hands-on role for someone who enjoys building, not just designing on paper. You should be deeply comfortable with Python-based systems, and have strong experience building cloud-native, microservices-driven platforms, including data pipelines and distributed systems.\nYou will work closely with product, ML, and platform teams to deliver enterprise-scale solutions, improve backend performance and reliability, and raise the technical bar through thoughtful design, ownership, and execution across teams.\nResponsibilities:\nTechnical Leadership & Hands-On Contribution\nDesign and implement backend services, data integration layers, and distributed systems using Python and modern frameworks.\nBuild scalable microservices and REST/gRPC APIs for both real-time and batch workloads.\nLead technical design and architecture reviews while remaining deeply hands-on with code.\nCreate and maintain clear technical documentation, including architecture diagrams, component flows, design docs, and API specs.\nCommunicate technical decisions clearly to engineers, product partners, and non-technical stakeholders.\nAgentic Systems & AI-Native Architecture\nDesign and build agent-first systems where LLMs reason, plan, and act alongside deterministic services.\nImplement and evaluate agentic frameworks such as LangGraph, CrewAI, AutoGen, or similar open-source tools.\nApply agentic design patterns including planners, routers, evaluators, memory, tool-use, and feedback loops.\nIntegrate Model Context Protocols (MCP) or equivalent mechanisms to standardize tool access, context sharing, and orchestration across agents.\nBalance probabilistic AI behavior with deterministic workflows to ensure reliability, observability, and production safety.\nCollaborate closely with ML teams to move models from experimentation into scalable, production-grade systems.\nCloud-Native Development\nBuild and deploy services on AWS using EC2, Lambda, RDS, S3, DynamoDB, and managed AI services where appropriate.\nDesign systems using Kubernetes, containers, serverless, and event-driven patterns.\nEnsure reliability, observability, security, and cost awareness across cloud workloads.\nETL & Data Pipelines\nDesign data-intensive systems including ingestion pipelines, stream processing, and transformation workflows.\nWork with tools such as Apache Kafka, Airflow, Dagster, AWS Step Functions, or equivalent orchestration frameworks.\nDesign and operate systems using multiple databases such as MongoDB, OpenSearch/Elasticsearch, PostgreSQL, and similar technologies.\nCode Quality, CI/CD & Operational Excellence\nWrite high-quality, testable code with strong unit and integration test coverage.\nBuild and maintain Git-based CI/CD pipelines to support fast, reliable releases.\nOwn production outcomes by monitoring systems, diagnosing issues, and fixing root causes.\nCollaboration & Mentorship\nWork closely with product managers, ML engineers, platform teams, and stakeholders to align on outcomes.\nMentor engineers, lead code reviews, and raise the engineering bar through example.\nAdvocate for security-first development, operational discipline, and strong engineering culture.\nQualifications:\nBachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n8 - 10 years of backend and data engineering experience with a strong focus on microservices and distributed systems.\nHands-on experience with cloud platforms such as AWS (Lambda, S3, EC2, RDS), Azure (Azure Functions, Blob Storage, Virtual Machines), or GCP (Cloud Functions, Cloud Storage, Compute Engine).\nStrong hands-on experience with Python and frameworks like Flask, FastAPI, or Django and related libraries/frameworks such as NumPy, Pandas, PyDantic etc.\nStrong knowledge of data engineering technologies, including ETL tools (Apache Spark, Apache Airflow, AWS Glue, Google Dataflow), data warehouses (Amazon Redshift, Google BigQuery, Snowflake), and big data platforms (Hadoop, Apache Kafka, Apache HBase).\nFamiliarity with asynchronous and synchronous integration patterns and frameworks (RESTful APIs, GraphQL, WebSockets).\nStrong understanding of system design patterns, caching, rate-limiting, and queuing mechanisms.\nProficiency in backend and server-side technologies such as:\nWeb frameworks: Flask, Django, FastAPI\nMessaging protocols: HTTP, AMQP\nDatabase systems: SQL (PostgreSQL, MySQL, Oracle), NoSQL (MongoDB, Cassandra, DynamoDB, OpenSearch), Graph Databases like MemGraph or Neo4j\nCaching systems: Redis, Memcached\nServerless computing: AWS Lambda, Azure Functions\nContainerization and orchestration: Docker, Kubernetes\nMCP, Claude Agents, Google ADK\nKnowledge of microservices architecture and design principles.\nExperience with version control systems such as Git and CI/CD pipelines.\nExperience in setting up and using automated testing tools and frameworks, such as Selenium, PyTest, or JUnit.\nAbility to create and maintain detailed sequence diagrams and architectural documentation.\nProficiency in developing effective strategies to debug issues that arise in production environments.\nAbility to work collaboratively with cross-functional teams.\nAbility to adapt to new technologies and methodologies quickly.\nStrong problem-solving skills and attention to detail.\nExcellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.\nCareer Progression:\nAt Accrete we value professional growth and development of our employees. As a Staff/Principal Engineer - Application, you will have access to a variety of career advancement opportunities and growth within the organization. We provide ongoing training, mentorship, and opportunities to take on leadership roles within your team and work with leaders across departments.\nWhy Join Us:\nInnovative Environment: Be part of a team that's at the forefront of technological innovation, utilizing GenAI and ML to create groundbreaking solutions.\nCollaborative Culture: Work in a collaborative environment where your ideas are valued, and you have the opportunity to make a real impact.\nWe provide a flexible work environment\nProfessional Growth: We're committed to your professional growth and development, offering opportunities for learning and advancement.\nCompetitive Compensation: Enjoy a competitive compensation and benefits package, including medical insurance.\nJoin us at Accrete ( https://www.accrete.ai) and help build the next generation of AI-native systems. 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