TekWissen LLC logo

Senior AI Search & Agentic Systems Engineer

TekWissen LLC

  • Santa Clara, CA
  • 4 days ago
  • $60.71–$62.85

Highlights

Our client is an American multinational information technology services and consulting company and is a leading provider of information technology, consulting, and business process outsourcing services, dedicated helping the world's leading companies build stronger businesses. We are looking for a Senior Software Engineer to design and build intelligent search and agentic automation systems that combine traditional full-stack engineering with modern AI capabilities.

Numbers & Facts

LocationSanta Clara, CA
IndustryComputer/IT Services
Salary$60.71–$62.85
Company Size100 to 499 employees
Year Founded2009
Websitehttp://www.tekwissen.com/

Description

Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client is an American multinational information technology services and consulting company and is a leading provider of information technology, consulting, and business process outsourcing services, dedicated helping the world's leading companies build stronger businesses.
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Job Title: Senior AI Search & Agentic Systems Engineer
Location: Santa Clara, CA
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Onsite

Job Description:

  • We are looking for a Senior Software Engineer to design and build intelligent search and agentic automation systems that combine traditional full-stack engineering with modern AI capabilities.
  • You'll work across the stack - from backend services and data pipelines to AI-driven retrieval and agent orchestration - to deliver high-impact, production-grade solutions.

Key Responsibilities:

  • Design, develop, and maintain backend services using Java (Spring Boot) and Python, ensuring scalability, reliability, and performance.
  • Build and enhance React.js front-end applications with clean, responsive, and intuitive user interfaces.
  • Architect and optimize search solutions using Elasticsearch and Azure AI Search, including index design, query performance tuning, and relevance optimization.
  • Implement Retrieval-Augmented Generation (RAG) pipelines to power intelligent search and Q&A experiences, integrating vector search with LLM-based generation.
  • Design and deploy Claude-based agents and Claude Skills to automate workflows, orchestrate multi-step tasks, and integrate with internal/external systems.
  • Develop and manage data models and queries using PostgreSQL, ensuring efficient schema design and query performance.
  • Collaborate with cross-functional teams (product, data, DevOps) to translate business requirements into technical solutions.
  • Ensure best practices in code quality, testing, security, and CI/CD across all systems.
  • Monitor, troubleshoot, and optimize system performance in production environments.

Required Skills & Experience:

  • Strong proficiency in Python and Java (Spring Boot or equivalent frameworks).
  • Hands-on experience with React.js for front-end development.
  • Deep expertise in Elasticsearch - index design, aggregations, query DSL, performance tuning.
  • Experience with Azure AI Search (formerly Cognitive Search) - semantic search, vector indexing, hybrid search.
  • Practical experience building RAG (Retrieval-Augmented Generation) systems, including embedding generation, vector stores, and LLM integration.
  • Experience building or integrating Claude agents and Claude Skills (or similar LLM agent frameworks) for task automation.
  • Solid experience with PostgreSQL - schema design, optimization, and query writing.
  • Understanding of API design (REST/GraphQL) and microservices architecture.
  • Familiarity with cloud platforms (Azure preferred; AWS/GCP a plus).
  • Strong proficiency in Python and Java (Spring Boot or equivalent frameworks).
  • Hands-on experience with React.js for front-end development.
  • Deep expertise in Elasticsearch - index design, aggregations, query DSL, performance tuning.
  • Experience with Azure AI Search (formerly Cognitive Search) - semantic search, vector indexing, hybrid search.
  • Practical experience building RAG (Retrieval-Augmented Generation) systems, including embedding generation, vector stores, and LLM integration.
  • Experience building or integrating Claude agents and Claude Skills (or similar LLM agent frameworks) for task automation.
  • Solid experience with PostgreSQL - schema design, optimization, and query writing.

Nice to Have:

  • Experience with Kubernetes and containerized deployments.
  • Exposure to enterprise data pipelines (Databricks, Hadoop, or similar).
  • Prior experience integrating LLM-based tools into enterprise workflows (LMS, CRM, ERP systems).

Soft Skills:

  • Strong problem-solving and analytical thinking.
  • Ability to work independently and collaboratively in a fast-paced environment.
  • Excellent communication skills to work across engineering, product, and business teams.

Years of Experience:

  • 10-15 Years of Experience.

TekWissen Group is an equal opportunity employer supporting workforce diversity.

About Company

WE THE TEKWISSEN PEOPLE

TekWissen offers you a broader portfolio of services, industry-leading solutions, and the meaningful innovations that give you greater flexibility and speed to respond to market dynamics, reduced costs and risk to improve enterprise performance, and increased productivity to enable growth.

To keep pace with global market demands, TekWissen keeps its finger on the pulse of change. Our organized approach to guiding a project from its inception to closure. Managing projects is becoming more and more important as we enter the digital era. To cope with the pace that this transition demands, a method is required to manage projects so they can yield quality work, while incorporating efficient use of time and resources.

Project involves identifying which quality standards are relevant to the project and determining how to satisfy them.

It is important to perform quality planning during the Planning Process and should be done alongside the other project planning processes because changes in the quality will likely require changes in the other planning processes, or the desired product quality may require a detailed risk analysis of an identified problem. It is important to remember that quality should be planned, designed, then built in, not added on after the fact.

Capabilities and accomplishments in one TekWissen business enhance the opportunity for success in the others. Put simply, TekWissen's unique combination of attributes promotes success.



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