Talent Software Services
Talent Software Services

68 Talent Software Services Jobs Hiring Near You

Software Development & Technical Implementation * Design, develop, and refactor components using ASP.NET MVC, Entity Framework, and Azure App Service. * Contribute to CI/CD pipeline setup and ...

Code, compile, and implement application software that is delivered on time and within budget. Evaluate basic interrelationships in immediate programming area to determine how changes in one program ...

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Talent Software Services Jobs Information

What makes Talent Software Services an attractive place to work?

Talent Software Services is a reputable company in the software industry, known for its commitment to delivering innovative solutions to clients. The company's workplace is characterized by a collaborative environment that fosters creativity, open communication, and a culture of continuous learning, allowing employees to grow professionally and personally. By joining Talent Software Services, individuals can contribute to the development of cutting-edge software products and services, gain valuable experience, and advance their careers in a dynamic and supportive work environment.

What are the most popular states for Talent Software Services jobs?

What are the most popular job types at Talent Software Services?

Infographic showing various job openings at Talent Software Services in the United States as of August 2026, with employment types broken down into 12% Full Time, 1% Part Time, and 87% Contract. Highlights an 79% Physical, 9% Hybrid, and 12% Remote job distribution.

Senior AI Full Stack Developer

Talent Software Services

Boston, MA • On-site

Contractor

Posted 7 days ago


Job description

  • Job Title: Senior AI Full Stack Developer
  • Location: Boston, MA
  • Duration: 6 months
  • GBaMS ReqID: 10900647
  • Experience Required: 5–10 years of software engineering experience
  • Relevant AI Experience: 2+ years of hands-on experience with Generative AI, Agentic AI, or AI-powered enterprise applications
Overview
  • Design, develop, and deploy enterprise AI applications, intelligent agents, and data-driven solutions.
  • Leverage Generative AI, Azure AI services, and modern cloud data platforms.
  • Develop scalable, secure, and production-ready AI solutions.
  • Integrate AI capabilities with enterprise data platforms and business applications.
Key Responsibilities
  • Build AI-powered applications and agentic workflows.
  • Develop RAG-based knowledge, search, and document intelligence solutions.
  • Design and develop backend services, APIs, microservices, and integration components.
  • Integrate AI solutions with enterprise data platforms and business applications.
  • Develop data pipelines and AI workflows.
  • Build and deploy intelligent AI agents and enterprise copilots.
  • Deliver scalable, reliable, and production-ready AI solutions.
  • Take AI solutions from design and development through production deployment.
Must-Have Skills
  • Strong hands-on experience with Azure AI Foundry and Azure OpenAI.
  • Expertise in:
    • Retrieval-Augmented Generation (RAG)
    • Vector Databases
    • Prompt Engineering
    • Agentic AI
  • Experience with Agentic AI frameworks, including:
    • LangChain
    • Semantic Kernel
    • CrewAI
  • Strong proficiency in Python.
  • Strong experience with Snowflake and SQL.
  • Experience with data integration and cloud data platforms.
  • Strong enterprise API and microservices development experience.
  • Experience integrating AI applications with enterprise systems.
Nice-to-Have Skills
  • Databricks.
  • Snowflake Cortex.
  • Snowflake Cortex Agents.
  • Azure Machine Learning (Azure ML).
  • MLOps and model monitoring.
  • React.
  • Angular.
  • Experience in Manufacturing.
  • Experience in Supply Chain.
  • Experience in Life Sciences.
AI & Generative AI Expertise
  • Develop Generative AI applications using enterprise-grade LLM technologies.
  • Build RAG pipelines using vector databases and enterprise knowledge sources.
  • Develop and optimize prompts for LLM-based applications.
  • Build agentic workflows using LangChain, Semantic Kernel, CrewAI, or similar frameworks.
  • Integrate Azure OpenAI models into enterprise applications.
  • Develop AI-powered knowledge management, search, and document intelligence solutions.
  • Implement AI workflows that integrate with enterprise data and business processes.
Data Engineering & Integration
  • Develop scalable data pipelines to support AI and analytics workloads.
  • Integrate AI solutions with Snowflake-based data platforms.
  • Write optimized SQL queries for enterprise data processing.
  • Perform data extraction, transformation, and integration.
  • Work with structured and unstructured enterprise data.
  • Build AI-ready datasets and data workflows.
  • Integrate enterprise data sources with AI applications and services.
API & Backend Development
  • Design and develop enterprise-grade backend services.
  • Build REST APIs and microservices for AI applications.
  • Develop integration components between AI services and enterprise applications.
  • Implement scalable and secure API architectures.
  • Ensure reliability, performance, and maintainability of backend services.
Education & Experience
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • 5–10 years of software engineering experience.
  • 2+ years of hands-on experience building:
    • Generative AI applications
    • Agentic AI solutions
    • AI-powered enterprise applications
  • Experience integrating AI solutions with cloud data platforms and enterprise systems.
  • Strong software engineering and problem-solving skills.
Ideal Candidate
  • Hands-on AI engineer capable of independently building AI applications and intelligent agents.
  • Strong experience with Azure AI Foundry and Azure OpenAI.
  • Experienced in integrating AI solutions with Snowflake-based data platforms.
  • Capable of developing RAG pipelines, agentic workflows, AI applications, and data pipelines.
  • Strong backend, API, microservices, and cloud integration experience.
  • Able to take AI solutions from architecture and design through development, testing, and production deployment.
  • Strong ability to deliver scalable, secure, and production-ready enterprise AI solutions.