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# Python Developer Phoenix

- **Company:** Sierra Business Solution LLC
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Automation of Tests, Cloud Engineering, Code Review, Encodings, Databases, Continuous Integration, DevOps, Distributed Systems, Github, Monitoring of Systems, Python (Programming Language), PostgreSQL, Metadata, Performance Tuning, Prometheus, Search Technologies, Secure Coding, Web Services, Enterprise Application Integration, Data Logging, Large Language Models, Grafana, Prompt Engineering, Generative AI, Backend, Git, Fastapi, AI Platforms, Kubernetes, Low Latency, Virtual Agents, Api Design, Restful APIs, Artificial Intelligence Markup Language (AIML), Docker, Jenkins, Microservices
- **Published:** August 31, 2026
- **Apply:** https://www.dice.com/job-detail/26fd05d2-bd0d-4641-ac61-3bd138cb05e4

## About the Role

Python & API Engineering

Strong hands-on experience with Python 3.11+ and production backend development.

Strong experience building secure, scalable REST APIs and microservices using FastAPI familiarity

with FlaskDjango is useful.

Strong understanding of asynchronous Python, API design, validation, error handling,

authenticationauthorization, and enterprise integration patterns.

Generative AI, RAG & Knowledge Infrastructure

Hands-on experience building enterprise Generative AI applications using LLMs, RAG, semantic

search, embeddings, and vector databases.

Strong experience with LangChain and LangGraph for agentic workflows, stateful orchestration, tool

calling, multi-step execution, and controlled agent runtimes.

Experience designing knowledge ingestion, document chunking, embedding generation, metadata enrichment, retrievalreranking, context assembly, grounded generation, and response validation pipelines. Experience with PostgreSQL and vector search pgvector experience is highly desirable. Strong understanding of prompt engineering, AI agents, guardrails, human-in-the-loop patterns, AI evaluation, responsible AI, and secure enterprise data access. Platform Engineering, DevOps & Observability Strong hands-on experience with Docker and Kubernetes for production AI services. Experience with Git, GitHub ActionsJenkins and CICD pipelines for automated build, test and deployment. Experience with production monitoring and observability using OpenTelemetry, Prometheus, Grafana, SplunkELK or equivalent tools. Ability to troubleshoot performance, reliability, retrieval quality, API, infrastructure, and production issues across distributed AI systems. Strong analytical, problem-solving, documentation and
cross-functional communication skills.

DESIRABLE_SKILLS

Strong ownership and stakeholder management ability to work across Product, Architecture, AIML,

Data, Security and DevOps teams clear technical communication mentoring and code-review

capability analytical problem solving Agile delivery focus on reliability, security, scalability and

maintainability.

KEYWORDS

Python 3.11, FastAPI, LangChain, LangGraph, Generative AI, LLM, RAG, Retrieval Augmented

Generation, AI Agents, Agentic AI, Prompt Engineering, Semantic Search, Embeddings, Vector

Database, pgvector, PostgreSQL, Knowledge Base, Knowledge Platform, Document Ingestion,

Chunking, Retrieval, Reranking, Docker, Kubernetes, GitHub Actions, Jenkins, CICD,

OpenTelemetry, Prometheus, Grafana, AI Evaluation, Guardrails, REST API

EXPERIENCE_RANGE_IN_REQUIRED_SKILLS

5-6 Years

Role Descriptions: Python & API Engineering Strong hands-on experience with Python 3.11+ and production backend development. Strong experience building secure scalable REST APIs and microservices using FastAPI familiarity with FlaskDjango is useful. Strong understanding of asynchronous Python API design validation error handling authenticationauthorization and enterprise integration patterns.Generative AI RAG & Knowledge Infrastructure Hands-on experience building enterprise Generative AI applications using LLMs RAG semantic search embeddings and vector databases. Strong experience with LangChain and LangGraph for agentic workflows stateful orchestration tool calling multi-step execution and controlled agent runtimes. Experience designing knowledge ingestion document chunking embedding generation metadata enrichment retrievalreranking context assembly grounded generation and response validation pipelines. Experience with PostgreSQL and vector search pgvector experience is highly
desirable. Strong understanding of prompt engineering AI agents guardrails human-in-the-loop patterns AI evaluation responsible AI and secure enterprise data access.

Essential Skills: Python & API Engineering Strong hands-on experience with Python 3.11+ and production backend development. Strong experience building secure scalable REST APIs and microservices using FastAPI familiarity with FlaskDjango is useful. Strong understanding of asynchronous Python API design validation error handling authenticationauthorization and enterprise integration patterns.Generative AI RAG & Knowledge Infrastructure Hands-on experience building enterprise Generative AI applications using LLMs RAG semantic search embeddings and vector databases. Strong experience with LangChain and LangGraph for agentic workflows stateful orchestration tool calling multi-step execution and controlled agent runtimes. Experience designing knowledge ingestion document chunking embedding generation metadata enrichment retrievalreranking context assembly grounded generation and response validation pipelines. Experience with PostgreSQL and vector search pgvector experience is highly desirable.
Strong understanding of prompt engineering AI agents guardrails human-in-the-loop patterns AI evaluation responsible AI and secure enterprise data access.

Desirable Skills:

Keyword:

Skills: Digital : Python

## Description

Design, develop, maintain and evolve enterprise knowledge-base infrastructure and AI-enabled

backend services using Python and FastAPI.

Build and optimize ingestion, chunking, embedding, vector indexing, semantic retrieval, reranking,

context construction and grounded RAG pipelines.

Develop LangChainLangGraph-based agent workflows and reusable agent-runtime capabilities

including tool calling, state management, retries, validation, guardrails and human approval where

required.

Integrate LLMs and enterprise knowledge sources securely through reusable APIs and services.

Implement PostgreSQLvector database persistence, metadata filtering and retrieval patterns

optimized for accuracy, latency and scale.

Cloud-Native Delivery & Production Engineering

Containerize services with Docker and deploymanage them on Kubernetes.

Build and maintain CICD pipelines using GitHub Actions, Jenkins or equivalent tools, including

automated testing and deployment controls.

Implement logging, tracing, metrics, dashboards and alerts using OpenTelemetry, Prometheus,

Grafana and enterprise monitoring tools.

Diagnose and resolve issues across APIs, retrieval pipelines, agent execution, databases, containers

and distributed infrastructure.

Improve performance, reliability, security, scalability and cost efficiency of production AI services.

Quality, Evaluation & Collaboration

Establish automated tests and evaluation approaches for APIs, retrieval quality, grounded responses

and agent behavior.

Apply secure coding, access controls, audit logging, promptoutput validation and responsible-AI


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