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Manager Streamlit Jobs in Texas (NOW HIRING)

... managed secrets, and proper cost controls * Build lightweight UIs (Streamlit, Gradio, or React) for agentic applications and internal tools * Lead design reviews and cross-functional enablement ...

... Trial Managers to develop and validate data products that increase operational efficiency ... Experience building web applications is preferred (with either Shiny or Streamlit); and

Deploy and manage machine learning & data pipelines in production environments. * Work on ... RShiny, Streamlit, Python DASH, Tableau, PowerBI). * Familiarity with data privacy standards ...

Deploy and manage machine learning & data pipelines in production environments. * Work on ... RShiny, Streamlit, Python DASH, Tableau, PowerBI). * Familiarity with data privacy standards ...

... Trial Managers to develop and validate data products that increase operational efficiency ... Experience building web applications is preferred (with either Shiny or Streamlit); and

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Manage the Snowflake environment to ensure cost-efficiency and performance. This includes warehouse ... Proficient in Python for scripting, API interaction and Streamlit apps * Version Control: Strong ...

Use Infrastructure as Code (IaC) tools, like Terraform, to manage and automate Snowflake ... Streamlit to build agentic, AI-powered applications, reducing manual engineering effort and ...

Showing results 41-60

Manager Streamlit information

What is the difference between Manager Streamlit vs Data Analyst?

AspectManager StreamlitData Analyst
Required CredentialsBachelor's degree in CS, Data Science, or related field; experience with Streamlit and project managementBachelor's degree in Statistics, Data Science, or related field; proficiency in data analysis tools
Work EnvironmentCollaborative teams, project-based, tech-focusedData-focused, reporting, and insights generation
Employer & Industry UsageTech companies, startups, data-driven organizationsBusiness, finance, healthcare, and marketing sectors

The main difference is that a Manager Streamlit oversees the development and deployment of data apps using Streamlit, managing teams and projects, while a Data Analyst focuses on analyzing data, generating reports, and providing insights. Both roles require technical skills, but the Manager Streamlit role emphasizes project management and app development leadership.

What are the most commonly searched types of Streamlit jobs in Texas? The most popular types of Streamlit jobs in Texas are:
What cities in Texas are hiring for Manager Streamlit jobs? Cities in Texas with the most Manager Streamlit job openings:
Infographic showing various Manager Streamlit job openings in Texas as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Senior, Tax Technology Services - Agentic Engineering Platform for GESTC

Deloitte

Dallas, TX • On-site

$121K - $159K/yr

Full-time

Re-posted 18 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

Are you someone who wants hands-on experience building the tooling and knowledge infrastructure behind an agentic software development lifecycle? Are you ready to take the next step in your career by building integrations and knowledge bases that other engineering teams will depend on every day? Are you ready to work alongside experienced engineers on a small, high-visibility platform team? If the answer to all of the above questions is "Yes," come join the world's leading professional services firm. If you are prepared and poised to take the next step in your career, you can help build the platform that powers agentic software delivery across a global business. Then we want to talk to you.

Work you'll do

As a Senior Consultant, Agentic Engineering Platform, you will work alongside the team's Manager and other engineers to build the infrastructure that underpins our agentic software development lifecycle. Day to day, you will write Python to build APIs, automate workflows, and clean and structure the data (both structured and unstructured) that feeds our knowledge bases and tooling. You will build retrieval-augmented generation pipelines against vector databases, using embeddings and evaluation techniques to keep the LLM Wiki and AWS Bedrock-managed knowledge bases accurate and grounded. You will use LangChain, LangGraph, or a comparable orchestration framework to build the agents and stateful workflows that let AWS Kiro read program artifacts such as epics, features, and user stories out of Azure DevOps and turn them into working code. You will also help build integrations between ServiceNow and Azure DevOps that create defects automatically and route pull request assignments to the right developers, and you will build lightweight interfaces, using tools such as Streamlit, Gradio, or React, so engineers and technical program managers can use what you build without touching raw APIs. Beyond these integrations, you will build tools, utilities, and workflows, drawing on pandas, NumPy, and SQL, that help technical program managers identify risk and cross-project dependencies by processing information across the platforms our programs already use. The ideal candidate is a dependable team player who is eager to grow their engineering craft while contributing directly to a platform other teams rely on.  Core responsibilities of the role include:

  • Build data and knowledge foundations that prepare structured and unstructured information for the LLM Wiki and AWS Bedrock-managed knowledge bases.
  • Engineer grounded AI capabilities by developing retrieval-augmented generation pipelines, agentic workflows, evaluation harnesses, and guardrails that improve accuracy, reliability, and safety.
  • Connect the agentic software development lifecycle by integrating AWS Kiro, Azure DevOps, ServiceNow, and related platforms to automate the flow of program artifacts, defects, pull requests, and code updates.
  • Develop production-ready platform capabilities including backend services, APIs, lightweight user interfaces, deployment pipelines, logging, and monitoring that enable teams to use tools without direct API access.
  • Deliver iterative, well-documented solutions that improve visibility into program risks and dependencies, reduce manual effort, and help engineering and technical program management teams adopt and extend the platform.

A successful candidate would possess these skills:

  • Communicates clearly and confidently with technical and non-technical audiences, translating complex ideas, trade-offs, and priorities into simple language.
  • Collaborates effectively across teams by building trust, aligning stakeholders, and moving work forward in a fast-paced, cross-functional environment.
  • Shows initiative and sound judgment by staying organized, adapting quickly to changing needs, and delivering high-quality work with minimal direction.

The team

At Deloitte Tax LLP, our Global Employer Services (GES) Technology Group consultants help multinational clients develop programs, processes and digital offerings to manage a global workforce and the compliance obligations arising from global mobility, business travel and remote working. People within our technology group come from a diverse background - they partner with our go-to-market teams and global clients to solve challenging problems and design experiences and products that anticipate what our Deloitte clients will want and solutions that keep them compliant with global and local regulations.

Qualifications

Required:

  • Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co-locate in person 2 - 3 days per week
  • Bachelor's degree in computer science, information technology, engineering, or a related field.
  • 3+ years of hands-on Python experience, including building APIs, writing automated tests, debugging, and scripting for automation.
  • Experience with SQL and data preprocessing, including data cleaning, feature handling, and working with both structured and unstructured data.
  • Working knowledge of core data science libraries such as pandas, NumPy, and scikit-learn, with basic exposure to visualization libraries such as Matplotlib or Seaborn for analysis and evaluation.
  • Solid understanding of LLM and generative AI fundamentals, including prompting, embeddings, retrieval-augmented generation, vector databases, evaluation methods, guardrails, and hallucination management.
  • Experience building chains, tools, or agents with LangChain, LangGraph, or a comparable orchestration framework for stateful AI workflows.
  • Experience using AWS services programmatically via Boto3, including S3, Lambda, Bedrock, DynamoDB, and Agent Core, to support deployment workflows.
  • Experience with API integrations across at least two enterprise platforms (for example, Azure DevOps, ServiceNow, Jira, Confluence).
  • Experience with backend deployment practices, including FastAPI, Docker, CI/CD, logging, and monitoring.
  • Limited immigration sponsorship may be available.
  • Ability to travel up to 20%, on average, based on the work you do and the clients and industries/sectors you serve.
  • One of the following active accreditations obtained in process, or willing/able to obtain:
    • Licensed CPA in state of practice/primary office if eligible to sit for the CPA
    • If not CPA eligible:
      • Licensed attorney
      • Enrolled Agent
      • AWS Certified Solutions Architect
      • Certified Information Systems Security Professional (CISSP)
      • Certified SAFe Agile Software Engineer
      • Certified SAFe DevOps Practitioner
      • ISTQB (International Software Testing Qualifications Board)
      • Microsoft Azure
      • Microsoft Certified Solutions Developer (MCSD)
      • Oracle Certified Professional

Preferred:

  • Experience building usable interfaces for AI-powered tools using Streamlit, Gradio, React, or similar front-end frameworks
  • Familiarity with LLM evaluation and AI development workflows using tools such as DeepEval, RAGAS, AWS Kiro, GitHub Copilot, Claude Code, or similar.
  • Experience integrating platforms and automation workflows using Azure DevOps and ServiceNow APIs, webhooks, or connectors.
  • Prior experience supporting internal engineering teams or transformation efforts, including modernization initiatives and translating technical program management needs such as risk and dependency tracking into working software.
  • Strong software engineering and collaboration skills, including writing clean, well-tested code, contributing constructively in code reviews, and communicating effectively across technical and non-technical teams.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $102,750 to $195,250.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Are you someone who wants hands-on experience building the tooling and knowledge infrastructure behind an agentic software development lifecycle? Are you ready to take the next step in your career by building integrations and knowledge bases that other engineering teams will depend on every day? Are you ready to work alongside experienced engineers on a small, high-visibility platform team? If the answer to all of the above questions is "Yes," come join the world's leading professional services firm. If you are prepared and poised to take the next step in your career, you can help build the platform that powers agentic software delivery across a global business. Then we want to talk to you.

Work you'll do

As a Senior Consultant, Agentic Engineering Platform, you will work alongside the team's Manager and other engineers to build the infrastructure that underpins our agentic software development lifecycle. Day to day, you will write Python to build APIs, automate workflows, and clean and structure the data (both structured and unstructured) that feeds our knowledge bases and tooling. You will build retrieval-augmented generation pipelines against vector databases, using embeddings and evaluation techniques to keep the LLM Wiki and AWS Bedrock-managed knowledge bases accurate and grounded. You will use LangChain, LangGraph, or a comparable orchestration framework to build the agents and stateful workflows that let AWS Kiro read program artifacts such as epics, features, and user stories out of Azure DevOps and turn them into working code. You will also help build integrations between ServiceNow and Azure DevOps that create defects automatically and route pull request assignments to the right developers, and you will build lightweight interfaces, using tools such as Streamlit, Gradio, or React, so engineers and technical program managers can use what you build without touching raw APIs. Beyond these integrations, you will build tools, utilities, and workflows, drawing on pandas, NumPy, and SQL, that help technical program managers identify risk and cross-project dependencies by processing information across the platforms our programs already use. The ideal candidate is a dependable team player who is eager to grow their engineering craft while contributing directly to a platform other teams rely on.  Core responsibilities of the role include:

  • Build data and knowledge foundations that prepare structured and unstructured information for the LLM Wiki and AWS Bedrock-managed knowledge bases.
  • Engineer grounded AI capabilities by developing retrieval-augmented generation pipelines, agentic workflows, evaluation harnesses, and guardrails that improve accuracy, reliability, and safety.
  • Connect the agentic software development lifecycle by integrating AWS Kiro, Azure DevOps, ServiceNow, and related platforms to automate the flow of program artifacts, defects, pull requests, and code updates.
  • Develop production-ready platform capabilities including backend services, APIs, lightweight user interfaces, deployment pipelines, logging, and monitoring that enable teams to use tools without direct API access.
  • Deliver iterative, well-documented solutions that improve visibility into program risks and dependencies, reduce manual effort, and help engineering and technical program management teams adopt and extend the platform.

A successful candidate would possess these skills:

  • Communicates clearly and confidently with technical and non-technical audiences, translating complex ideas, trade-offs, and priorities into simple language.
  • Collaborates effectively across teams by building trust, aligning stakeholders, and moving work forward in a fast-paced, cross-functional environment.
  • Shows initiative and sound judgment by staying organized, adapting quickly to changing needs, and delivering high-quality work with minimal direction.

The team

At Deloitte Tax LLP, our Global Employer Services (GES) Technology Group consultants help multinational clients develop programs, processes and digital offerings to manage a global workforce and the compliance obligations arising from global mobility, business travel and remote working. People within our technology group come from a diverse background - they partner with our go-to-market teams and global clients to solve challenging problems and design experiences and products that anticipate what our Deloitte clients will want and solutions that keep them compliant with global and local regulations.

Qualifications

Required:

  • Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co-locate in person 2 - 3 days per week
  • Bachelor's degree in computer science, information technology, engineering, or a related field.
  • 3+ years of hands-on Python experience, including building APIs, writing automated tests, debugging, and scripting for automation.
  • Experience with SQL and data preprocessing, including data cleaning, feature handling, and working with both structured and unstructured data.
  • Working knowledge of core data science libraries such as pandas, NumPy, and scikit-learn, with basic exposure to visualization libraries such as Matplotlib or Seaborn for analysis and evaluation.
  • Solid understanding of LLM and generative AI fundamentals, including prompting, embeddings, retrieval-augmented generation, vector databases, evaluation methods, guardrails, and hallucination management.
  • Experience building chains, tools, or agents with LangChain, LangGraph, or a comparable orchestration framework for stateful AI workflows.
  • Experience using AWS services programmatically via Bo...

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