Python developer - Dallas, Tx
At a glance
Mid-level Backend Engineering role at Fa Ertb Saasfaprod1. United States · $39,000–$137,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Build and maintain Python backend services and APIs that can scale with production needs
- Create agent workflows for autonomous decisions, task execution and multi-step reasoning
- Connect language models and external tools, then build RAG pipelines using vector stores and enterprise knowledge
- Add automated tests and evaluation checks, and improve latency, scale and infrastructure use
- Develop resilient platform services and Python connectors for APIs, databases and enterprise applications
What you bring
- At least ten years in software engineering, with strong Python development experience
- Hands-on work with agent frameworks such as LangGraph, CrewAI or another listed framework
- Experience delivering RAG applications and enterprise AI solutions
- Strong experience with REST APIs, microservices, event-driven systems and the listed AI, cloud and database technologies
Who this fits
This role suits a senior-level Python engineer focused on backend systems and agentic AI, despite the mid-level role bucket. It is not available to independent contractors; full-time employees can receive the listed benefits.
From the employer
The Senior Python Developer will play a key role in designing, developing, and scaling our Agentic AI platform. This role requires deep expertise in Python development, AI-driven application architectures, and cloud-native technologies to build robust, scalable, and production-ready agentic solutions.
You will be responsible for developing backend services, implementing agent orchestration workflows, integrating LLMs and external tools, and building resilient platforms that support enterprise AI use cases.
Key Responsibilities:
Backend Development: Design, develop, and maintain scalable backend services and APIs using Python and modern development frameworks.
Agentic AI Development: Build and support agent orchestration workflows that enable autonomous decision-making, task execution, and multi-step reasoning.
LLM Integration: Develop integrations with LLM providers such as OpenAI, Gemini, Anthropic, and open-source models to power AI-driven applications.
RAG Implementation: Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases and enterprise knowledge sources.
Platform Engineering: Develop resilient, high-performance platform services that support secure and scalable AI deployments.
Tool Integration: Create Python-based tools and connectors that enable agents to interact with APIs, databases, enterprise applications, and external services.
Testing & Evaluation: Implement automated testing, evaluation frameworks, and quality controls to ensure reliability and consistency of AI systems.
Performance Optimization: Optimize application performance, latency, scalability, and infrastructure utilization across AI workloads.
Required Skills & Qualifications:
- 10+ years of experience in software engineering with strong expertise in Python development.
- Strong experience developing REST APIs, microservices architectures, and event-driven systems.
- Hands-on experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, or Agent Development Kit (ADK).
- Experience building and supporting RAG-based applications and enterprise AI solutions.
- Strong knowledge of LangChain, LlamaIndex, LangSmith, and LangFlow.
- Experience working with LLMs including OpenAI, Gemini, Anthropic, Llama, or similar models.
- Deep understanding of prompt engineering, function calling, tool integration, agent orchestration, and evaluation techniques.
- Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus.
- Strong proficiency in PostgreSQL, MySQL, MongoDB, Redis, and database optimization techniques.
- Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native application development.
- Familiarity with Docker, Kubernetes, and containerized deployment patterns.
- Experience implementing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or GitLab CI.
- Experience with monitoring, logging, and observability tools for production systems.
Compensation, Benefits and Duration
Minimum Compensation: USD 39,000
Maximum Compensation: USD 137,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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