Design, develop, and deploy production-grade generative AI and agentic systems, including RAG pipelines, autonomous agents, prompt architectures, and enterprise integrations. Build solutions using LangChain, LangGraph, vector databases, cloud services, APIs, and DevOps tooling. Advise stakeholders, document and monitor AI applications, mitigate technical and security risks, modernize RPA assets, and mentor junior developers.
Developer Role and Responsibilities :
In this role, you will design, build, and deploy production-grade Generative AI and Agentic AI solutions that automate complex business processes and augment enterprise workflows. You will work across the full delivery lifecycle, from solution design and prompt/agent architecture through development, evaluation, and deployment, partnering closely with automation, data, and platform teams. Responsibilities will include hands-on development of LLM-powered applications, technical solutioning with stakeholders, and mentoring of junior developers on GenAI best practices. You will work closely with our team of award-winning business and technical specialists and leaders.
Key Responsibilities :
- Design and develop LLM-powered applications, including RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and multi-step autonomous agents using frameworks such as LangChain and LangGraph
- Build and optimize retrieval architectures using vector databases (e.g., ChromaDB) and semantic search to ground LLM responses in enterprise data.
- Apply prompt engineering techniques to improve accuracy, reliability, and cost-efficiency of LLM-based solutions across both hosted (OpenAI API, Claude Code, Claude) and offline/self-hosted models.
- Serve as a technical point of contact for clients and internal stakeholders on AI solution design, feasibility, and delivery timelines.
- Integrate GenAI solutions with existing enterprise systems via REST APIs, webhooks, and cloud services (AWS Lambda, Azure) to ensure secure, scalable deployment.
- Extend or modernize existing RPA/automation assets (e.g., Blue Prism, code-based automation frameworks) by incorporating AI-driven decisioning and self-healing capabilities.
- Coordinate the development, review, and documentation of AI solution deliverables (solution design documents, evaluation reports, deployment runbooks).
- Establish CI/CD and monitoring practices for AI applications using tools such as Git, GitHub Actions, Jenkins, and Splunk.
- Identify risks related to model performance, data quality, and security; mitigate roadblocks during development, testing, or deployment.
Qualifications and Skills
- Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent education and experience.
- Minimum 5–8 years of software development experience, including at least 2 years building Generative AI or Agentic AI applications in production.
- Hands-on experience with LLM application frameworks (LangChain, LangGraph) and LLM APIs (OpenAI API or equivalent).
- Strong understanding of RAG architectures, prompt engineering, and vector databases (e.g., ChromaDB or similar).
- Proficiency in Python; working knowledge of C#, JavaScript, and SQL.
- Experience with cloud platforms and services (AWS Lambda, Amazon DynamoDB, Azure) and REST API integration.
- Experience with DevOps tooling (Git/GitHub, GitHub Actions, Jenkins) and application monitoring (e.g., Splunk).
- Background in RPA or process automation (e.g., Blue Prism, UiPath, or Automation Anywhere) is a strong plus.
- Understanding of IT delivery methodologies (Agile, Lean, ITIL).
- Excellent planning, problem-solving, and technical leadership skills.
Desired characteristics in candidates :
- Self-motivated and able to take initiative with minimal supervision.
Senior AI Developer (Generative AI & Agentic Systems) - Effective communicator, able to translate technical AI concepts for non-technical stakeholders.
- Highly organized and methodical, while comfortable adapting to changing requirements.
- Strong analytical and problem-solving skills, with a bias toward experimentation and iteration.
- High emotional intelligence and cross-functional collaboration skills.
- Demonstrated willingness to dive into implementation details to guide projects to completion.
- Team-oriented, with an interest in mentoring and knowledge-sharing.
- Curious and committed to staying current with the fast-evolving GenAI/Agentic AI landscape.
Compensation and start dates
- Hiring now for immediate start
- Salary: Competitive base and bonus determined by level and experience
Similar Jobs
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develops and controls integrated project schedules for large-scale EPC, industrial construction, semiconductor fab, infrastructure, and related projects. Responsibilities include baseline management, critical path and delay analysis, schedule variance monitoring, recovery planning, contractor schedule validation, progress forecasting, stakeholder workshops, and executive reporting. The role coordinates engineering, procurement, construction, and commissioning teams while using Primavera P6, project controls methods, BI dashboards, and AI tools to support delivery decisions.
Top Skills:
ChatgptClaudeMicrosoft CopilotExcelMicrosoft PowerpointMicrosoft ProjectPower BIPrimavera P6Tableau
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Manages indirect material planning, procurement coordination, inventory accuracy, tooling orders and maintenance, and WIP management for semiconductor assembly and test operations. Drives manufacturing improvements through AI, automation, dashboards, and real-time issue resolution. Maintains process documentation, supports quality and regulatory compliance, and collaborates cross-functionally to improve production flow and achieve operational KPIs.
Top Skills:
Artificial IntelligenceAutomationDashboardsData Visualization SoftwareMesSAP
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Leads industrial engineering for semiconductor assembly and test manufacturing, including capacity and resource planning, labor optimization, operational excellence, cost reduction, manufacturing analytics, and factory systems. Develops capacity models, staffing standards, dashboards, and automation initiatives while supporting budgets and capital planning. Builds and mentors an industrial engineering team and collaborates globally to standardize manufacturing practices and improve efficiency, utilization, cycle time, and cost performance.
Top Skills:
Advanced AnalyticsAIManufacturing SimulationMesExcelPower BISQLTableau
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
