{"id":1139683,"url":"https://alion.io/job/synechron-tech-chapter-lead-python-aws-llm-engineering-microservices","title":"Tech Chapter Lead – Python, AWS, LLM Engineering & Microservices","company":{"id":5306,"name":"Synechron","domain":"synechron.com","url":"https://alion.io/company/synechron","size_band":"5000+","is_staffing_agency":true,"is_intermediary":false,"ats_vendor":"Workday","truth_index":{"grade":"A","score":92,"open_postings":13,"ghost_share":0,"stale_share":0.385,"repost_share":0.231,"time_to_fill_p50_days":17,"computed_at":"2026-09-23T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":63000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":636},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon ECS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"DynamoDB","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"IAM","optional":false},{"name":"JavaScript","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SonarQube","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-09-23T10:16:08Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-09-23T13:49:28Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Summary\nSynechron is seeking a Tech / Chapter Lead with 12 to 15 years of experience to provide hands-on engineering leadership across the Process Intelligence Engine (PIE) squads. The role is accountable for technical quality, architecture alignment, scale readiness, engineering standards, and delivery outcomes. The successful candidate will actively design, build, test, troubleshoot, review, and ship software. The role combines technical leadership with direct engineering contribution across Python, AWS cloud-native services, microservices, LLM integration, event-driven processing, and modern front-end technologies.\nFor the Chapter Lead role, management experience is required. The position will contribute to maintainable, secure, scalable, and production-ready solutions while guiding engineers across squads.\nSoftware Requirements\nRequired\nPython: Strong hands-on engineering experience in production software development.\nFastAPI: Experience building and maintaining Python-based services.\nREST APIs: Experience designing, developing, integrating, testing, and supporting RESTful services.\nReact and TypeScript: Experience developing or integrating front-end applications.\n AWS cloud-native services: ECSS3DynamoDBSQSSecrets ManagerIAMApplication Load Balancer (ALB)\nEnterprise LLM integration: Experience integrating enterprise LLM capabilities through AWS Bedrock / AI Gateway.\nLangGraph: Practical experience with LLM-powered workflow orchestration.\nLLM engineering: Experience with tool and function calling, structured outputs, evaluation, and observability.\nRedis: Experience supporting caching, low-latency access, or distributed application workflows.\nAsynchronous and event-driven processing: Experience designing and implementing non-blocking, message-based, or event-driven solutions.\nDocker: Experience containerizing and running applications.\nCI/CD: Experience supporting automated build, test, security, and deployment workflows.\nJFrog: Experience with artifact or package repository workflows.\nSonarQube: Experience with code-quality analysis and quality gates.\nMicroservices: Experience designing and delivering distributed services.\nCloud-native integration patterns: Experience connecting secure enterprise services and platforms.\nPreferred\nExperience with semantic and vector search.\nExperience with speech and transcript processing.\nExperience applying LLMs to production software and business workflows.\nExperience with LLM evaluation frameworks, monitoring, tracing, and production observability.\nExperience developing reusable engineering patterns across multiple squads.\nExperience managing engineers in a Chapter Lead or comparable people-management role.\nExperience working with enterprise process intelligence, automation, or workflow platforms.\nOverall Responsibilities\nProvide hands-on technical leadership across the PIE squads.\nDesign, build, test, troubleshoot, and ship production-ready software.\nEstablish engineering patterns, coding standards, integration practices, and quality expectations.\nGuide technical decisions and ensure alignment with the agreed architecture.\nReview implementations and pull requests for correctness, security, scalability, maintainability, and performance.\nDesign and develop Python-based microservices using FastAPI and REST APIs.\nBuild cloud-native solutions using AWS services, including ECS, S3, DynamoDB, SQS, Secrets Manager, IAM, and ALB.\nDevelop React and TypeScript components and support integration with backend services.\nIntegrate enterprise LLM capabilities through AWS Bedrock / AI Gateway.\nDevelop LLM-powered workflows using LangGraph, tool and function calling, structured outputs, and workflow orchestration.\nImplement semantic and vector search, LLM evaluation, observability, speech processing, and transcript processing where required.\nDesign asynchronous and event-driven processing using appropriate messaging and integration patterns.\nTroubleshoot complex technical issues across applications, integrations, infrastructure, data flows, and AI-enabled services.\nSupport CI/CD, Docker-based delivery, JFrog artifact management, and SonarQube quality controls.\nMentor engineers, demonstrate engineering patterns, and provide technical guidance across squads.\nFor the Chapter Lead role, manage engineering resources, support development planning, and contribute to team capability growth.\nImprove delivery quality, service reliability, scalability, maintainability, and operational readiness.\nPromote efficient use of cloud compute, storage, networking, and data resources to support sustainable engineering practices.\nTechnical Skills (By Category)\nProgramming Languages\nEssential\nPython with strong hands-on production engineering experience.\nTypeScript for front-end development or service integration.\nJavaScript knowledge relevant to React-based applications.\nPreferred\nAdditional programming or scripting experience for automation, testing, deployment, or data processing.\nExperience implementing reusable libraries, service components, or engineering accelerators.\nDatabases/Data Management\nEssential\nDynamoDB for cloud-based application data storage and retrieval.\nRedis for caching and low-latency data access.\nExperience designing data access patterns for microservices and distributed systems.\nUnderstanding of data structures, data flow, consistency, and scalability considerations.\nExperience supporting semantic and vector search where applicable.\nPreferred\nExperience with vector databases or vector-search platforms.\nExperience with speech, transcript, and unstructured data processing.\nExperience designing data solutions for high-volume or asynchronous workloads.\nCloud Technologies\nEssential\nAWS cloud-native engineering experience.\nECS for containerized application deployment.\nS3 for object storage and data handling.\nDynamoDB for cloud-based application data.\nSQS for asynchronous messaging.\nSecrets Manager for secure secrets management.\nIAM for identity and access control.\nApplication Load Balancer (ALB) for application traffic routing.\nUnderstanding of cloud-native integration patterns and scalable service design.\nPreferred\nExperience optimizing AWS workloads for availability, performance, cost, and resource efficiency.\nExperience with cloud monitoring, logging, tracing, and operational support.\nExperience supporting cloud migration or modernization initiatives.\nFrameworks and Libraries\nEssential\nFastAPI.\nReact.\nTypeScript.\nLangGraph.\nREST API frameworks and libraries.\nLibraries or services supporting enterprise LLM integration, structured outputs, tool and function calling, and workflow orchestration.\nPreferred\nFrameworks supporting semantic search, vector search, speech processing, transcript processing, and LLM evaluation.\nExperience developing reusable frameworks or shared components across engineering squads.\nDevelopment Tools and Methodologies\nEssential\nMicroservices architecture.\nAsynchronous and event-driven processing.\nDocker.\nCI/CD.\nJFrog.\nSonarQube.\nPull-request reviews and source-control workflows.\nProduction troubleshooting and operational support.\nHands-on software design, development, testing, and release practices.\nEngineering patterns and standards that support quality, scalability, and maintainability.\nPreferred\nExperience implementing automated testing, deployment validation, security checks, and quality gates.\nExperience establishing engineering standards across multiple teams.\nExperience with LLM evaluation and observability practices.\nExperience using structured development methods to support continuous delivery.\nSecurity Protocols\nEssential\nAWS IAM and secure access-control practices.\nAWS Secrets Manager and secure handling of credentials, keys, and sensitive configuration.\nSecure enterprise service integration.\nSecure REST API design and implementation.\nApplication security considerations across development, deployment, and operations.\nAbility to identify and address security risks in microservices, cloud infrastructure, APIs, data flows, and LLM integrations.\nPreferred\nExperience implementing security controls for enterprise AI services and LLM-powered workflows.\nExperience with security testing and remediation integrated into CI/CD pipelines.\nFamiliarity with secure handling of sensitive speech, transcript, or business-process data.\nExperience Requirements\n12 to 15 years of software engineering experience, including substantial hands-on development.\nStrong Python and AWS cloud-native engineering capability.\nExperience designing, developing, testing, troubleshooting, and shipping production software.\nExperience with Python, FastAPI, REST APIs, React, TypeScript, microservices, AWS services, Docker, CI/CD, and secure enterprise integration.\nPractical experience integrating LLMs into production software, including LLM-powered workflows, tool and function calling, structured outputs, evaluation, and observability.\nRequired for Chapter Lead Management experience, including mentoring, team support, engineering planning, or people-management responsibilities.\nPreferred Experience with semantic and vector search, speech and transcript processing, event-driven systems, and enterprise process intelligence.\nPreferred Experience leading technical delivery across multiple engineering squads.\nCandidates may also qualify through an equivalent combination of relevant professional experience, technical training, demonstrated engineering leadership, and delivery of comparable cloud-native and AI-enabled platforms.\nDay-to-Day Activities\nWork directly with the codebase to design, prototype, implement, test, troubleshoot, and ship Python, FastAPI, React, TypeScript, and AWS-based solutions.\nParticipate in architecture discussions, squad planning, technical reviews, pull-request reviews, delivery meetings, and collaboration with engineering and business stakeholders.\nDeliver microservices, REST APIs, LLM-powered workflows, event-driven integrations, infrastructure changes, automated tests, quality improvements, and technical documentation.\nMake technical decisions within agreed architecture and standards, guide engineers across squads, resolve delivery risks, and support scale, security, maintainability, and production readiness.\nQualifications\nA bachelor’s or master’s degree in Computer Science, Information Technology, Engineering, or a related field is preferred; equivalent relevant experience and demonstrated technical capability may be considered.\n12 to 15 years of software engineering experience, with strong hands-on Python and AWS cloud-native development experience.\nManagement experience is required for the Chapter Lead role, including team guidance, mentoring, resource planning, or people-management responsibilities.\nCertifications in AWS, cloud architecture, software development, security, or AI engineering are preferred but are not specified as mandatory.\nMaintain continuous professional development in Python, AWS, microservices, DevOps, secure integration, LLM engineering, evaluation, observability, and emerging AI technologies.\nProfessional Competencies\nApply structured critical thinking and problem-solving to address complex software, cloud, integration, scalability, security, and AI-engineering challenges.\nProvide technical leadership, mentorship, and practical guidance while contributing directly to engineering delivery.\nCommunicate technical decisions, risks, design options, progress, and trade-offs clearly with engineers, stakeholders, and cross-functional teams.\nAdapt to evolving technologies, requirements, AI capabilities, delivery priorities, and operational needs while maintaining quality.\nIdentify opportunities to improve engineering patterns, automation, LLM workflows, system performance, maintainability, and sustainable cloud-resource usage.\nManage priorities, dependencies, technical decisions, squad commitments, and delivery timelines while maintaining accountability for quality and production readiness.\nS YNECHRON’S DIVERSITY...","description_format":"text","description_chars":13110,"description_truncated":true,"requirements":{"experience_years_min":12,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Flexible schedule","Professional 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