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Python Ai Jobs in Austin, TX (NOW HIRING)

Cotality

Principal Software Engineer (Python)

Austin, TX · On-site +1

$133K - $179K/yr

Develop High-Performance AI Services: Utilize Git or similar, Unix command line, Python, FastAPI, FastMCP, and ADK to build and enhance robust backend services that bridge core enterprise data with ...

Apple

GenAI Physical Synthesis Engineer

Austin, TX · On-site

$134K - $138K/yr

Experience with GenAI frameworks, large language models, and AI agent developmentExperience with industry standard Synthesis tools such as Fusion Compiler or GenusScripting skills in TCL, Python, or ...

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All JobsPython Ai JobsPython Ai Jobs in Austin, TX

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How much do python ai jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for python ai in Austin, TX is $58.11, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

For a Python AI developer, roles that require complex problem-solving, creativity, and human interaction are more likely to persist, such as AI research scientist, data scientist, and machine learning engineer. These jobs involve designing, interpreting, and improving AI systems, often requiring specialized knowledge, critical thinking, and domain expertise that are difficult for AI to fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience in this field.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI architect, often requiring advanced skills in programming, data analysis, and deep learning. Such roles usually involve leadership responsibilities, extensive experience, and may be found in large tech companies or specialized AI firms with competitive compensation packages.

What is a Python AI job?

A Python AI job involves developing, implementing, and optimizing artificial intelligence models using Python. Professionals in this role work with machine learning frameworks like TensorFlow, PyTorch, and scikit-learn to build automation, predictive analytics, and AI-driven solutions. Responsibilities may include data preprocessing, model training, fine-tuning algorithms, and deploying AI models into production. These roles are common in industries like healthcare, finance, and tech, where AI is used for tasks such as natural language processing, computer vision, and recommendation systems.

What are the key skills and qualifications needed to thrive in the Python Ai position, and why are they important?

To thrive as a Python AI professional, you need strong programming skills in Python, a solid understanding of machine learning algorithms, data structures, and often a degree in computer science or a related field. Proficiency with libraries like TensorFlow, PyTorch, scikit-learn, and experience using version control systems such as Git are typically required, while certifications in AI or data science can be advantageous. Analytical thinking, problem-solving abilities, and effective communication skills help you interpret results and collaborate with multidisciplinary teams. These competencies enable the development, deployment, and optimization of AI-driven solutions in a fast-evolving technical landscape.

Will AI replace Python coders?

AI tools can automate certain coding tasks, but Python coders are still essential for designing, developing, and maintaining complex software systems. AI may augment programming work, but human expertise remains critical for problem-solving, creativity, and understanding project requirements.

What are the typical daily responsibilities of a Python AI professional?

As a Python AI professional, your day-to-day responsibilities usually involve designing, developing, and testing machine learning models, cleaning and analyzing data, and implementing data pipelines. You’ll likely collaborate closely with data scientists, software engineers, and product managers to integrate AI solutions into real-world applications. Regular tasks also include code review, documentation, and participating in team meetings to review progress and brainstorm solutions to technical challenges. These activities not only foster collaboration but also ensure high-quality, scalable AI products.

Can you do AI with Python?

Python AI refers to developing artificial intelligence applications using the Python programming language, which is widely used in the field due to its simplicity and extensive libraries like TensorFlow, PyTorch, and scikit-learn. AI development with Python involves tasks such as machine learning, deep learning, and data analysis, often requiring knowledge of algorithms, data structures, and programming skills. Many AI roles for Python developers focus on model building, data processing, and deploying AI solutions in various industries.
What are the most commonly searched types of Python Ai jobs in Austin, TX? The most popular types of Python Ai jobs in Austin, TX are:
What are popular job titles related to Python Ai jobs in Austin, TX? For Python Ai jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Python Ai jobs in Austin, TX look for? The top searched job categories for Python Ai jobs in Austin, TX are:
What cities near Austin, TX are hiring for Python Ai jobs? Cities near Austin, TX with the most Python Ai job openings:
Python Ai jobs near you
Infographic showing various Python Ai job openings in Austin, TX as of June 2026, with employment types broken down into 43% Full Time, 31% Part Time, and 26% Contract. Highlights an 100% In-person job distribution, with an average salary of $120,861 per year, or $58.1 per hour.

SAP BTP - Python AI

Futran Tech Solutions Pvt. Ltd.

Austin, TX • On-site

Full-time

Posted 6 days ago

Job description

Austin, TX.
Rate: Standard as per market.
This requirement is having skills combination Python with Gen AI & SAP BTP also. Full JD below.
JD:
  • Design, govern, and scale SAP BTP-based enterprise solutions, while embedding GenAI into workflows, operations, and user experiences
  • The role requires platform architecture, cloud-native design, integration, security, and GenAI-driven automation
  • Hands-on experience with SAP BTP architecture and ability to embed GenAI and agentic AI capabilities into SAP-centric enterprise landscape

Skills:
SAP BTP & Cloud
  • 8-10+ years of experience in SAP or enterprise cloud architecture
  • Strong hands-on experience with SAP BTP services
  • Solid understanding of cloud-native and microservices architecture
  • Experience with SAP security and identity concepts

GenAI & AI Architecture
  • Practical experience designing or implementing GenAI solutions
  • Strong understanding of:
    • LLMs and prompt engineering
    • RAG architectures
    • AI orchestration / agent-based patterns
  • Experience integrating LLMs with enterprise systems and APIs

DevSecOps & Engineering
  • Experience with CI/CD, automation, and cloud operations
  • Familiarity with Kubernetes, APIs, and event-driven architectures
  • Understanding of observability and reliability for production systems

Good to Have
  • Experience with SAP AI Core / AI Launchpad / GenAI Hub
  • Exposure to frameworks like LangChain, LangGraph, CrewAI

Responsibilities
SAP BTP & Cloud
  • Design and own end-to-end SAP BTP architectures across:
    • Cloud Foundry and/or Kyma runtimes
    • SAP Integration Suite (CPI, API Management, Event Mesh)
    • SAP HANA Cloud, Datasphere
    • Identity & Access Management (IAS, XSUAA, IDP trust)
  • Define account, subaccount, runtime, and security models aligned with enterprise standards
  • Establish reference architectures, design patterns, and best practices for BTP implementations

GenAI & AI Architecture
  • Design and implement GenAI-enabled use cases on BTP, such as:
    • AI copilots for SAP users
    • Incident, alert, and change summarization
    • Automated root cause analysis and remediation recommendations
    • Knowledge bots for runbooks, KT documents, and SAP operations
  • Architect RAG (Retrieval-Augmented Generation) pipelines using:
    • SAP HANA Cloud / vector stores
    • Secure enterprise data sources
  • Integrate BTP with enterprise LLM platforms (Azure OpenAI, OpenAI, Gemini, etc.)
  • Evaluate and apply agentic AI patterns

DevSecOps & Engineering
  • Define CI/CD pipelines for BTP applications and AI workflows
  • Ensure production readiness of GenAI solution
  • Work closely with SRE / Ops teams to operationalize AI solutions at scale

Apply