Python AI Engineer (Prompt & Agentic Systems)

Atlanta, GA, US • Posted 7 hours ago • Updated 3 minutes ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Generative AI applications
  • API Integrations
  • Prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • Docker & Kubernetes
  • Weaviate
  • Data privacy & PII handling
  • LLM fine-tuning approaches
  • Python AI Engineer
  • LLM Engineering
  • Agentic AI Systems
  • Multi-Agent Workflows
  • FastAPI / Backend APIs
  • AI Microservices
  • Tool / Function Calling
  • Agent Orchestration Frameworks
  • LangChain / LangGraph / AutoGen
  • Vector Databases (FAISS
  • Pinecone
  • Chroma)
  • CI/CD for AI Services
  • Prompt Injection Prevention
  • Azure OpenAI / AWS / GCP AI
  • Access Control & Secrets Management
  • AI Safety & Risk Mitigation
  • Embeddings & Semantic Search
  • Hybrid Search & Re-ranking
  • Memory & Planning Agents
  • Observability & Telemetry
  • Tooling & Workflow Engines

Summary

Solution IT Inc. is looking for a Python AI Engineer (Prompt & Agentic Systems) for one of its clients Atlanta, GA (3 days/week onsite)

Job Title: Python AI Engineer (Prompt & Agentic Systems)

Summary

We're looking for a hands-on engineer who can build AI-enabled applications end-to-end using Python, with strong skills in prompt engineering and agentic system design (multi-agent/orchestrated AI workflows). You'll design, develop, and productionize intelligent features-ranging from retrieval-augmented generation (RAG) to autonomous tasking agents integrated with internal tools and APIs.

Responsibilities:

  • Design & Build AI Services: Develop Python-based back-end services that integrate LLMs for reasoning, extraction, summarization, and decision support.
  • Prompt Engineering: Craft, version, and evaluate prompts/system instructions; design guardrails, test prompt variants, and optimize for reliability, latency, and cost.
  • Agentic Systems: Architect and implement autonomomulti-agent workflows-planning, tool-use, memory, error recovery, and human-in-the-loop controls.
  • RAG Pipelines: Implement document ingestion, chunking, embeddings, vector search (semantic/re-ranking), and grounding strategies.
  • Evaluation & Observability: Define metrics and build eval suites for quality (accuracy, factuality, safety), and establish tracing/telemetry for LLM calls.
  • API & Tool Integrations: Enable agents to use tools (internal APIs, search, databases, workflow engines); handle auth, rate limits, and fallbacks.
  • MLOps / AIOps: Package, containerize, and deploy services (Docker/K8s); manage keys, secrets, CI/CD; support canary rollouts and cost governance.
  • Security & Compliance: Apply data privacy principles, PII handling, redaction, prompt injection defenses, and audit logging.
  • Cross-Functional Collaboration: Partner with product, data, and security teams to translate requirements into reliable AI features.

Required Skills

  • Strong Python (typing, async, testing, packaging) and experience building production APIs/services (FastAPI/Flask).
  • Hands-on with LLMs (OpenAI, Azure OpenAI, Anthropic, etc.) and embedding/RAG workflows.
  • Proven prompt engineering experience (few-shot strategies, tool-use instructions, output schemas, function/tool calling).
  • Experience with agent frameworks or custom agent orchestration (e.g., Lang Graph /Lang Chain/Auto Gen, or in-house equivalents).
  • Vector databases (e.g., FAISS, Chroma, Pinecone, Weaviate) and search relevance tuning.
  • Familiar with MLOps/DevOps: Docker, CI/CD, monitoring (PrometheGrafana), logging (OpenTelemetry), secrets management.
  • Testing & Evals: unit/integration tests, offline evals, golden datasets, regression checks.
  • Practical understanding of AI safety/guardrails (prompt injection, data leakage, jailbreak prevention).

Nice to Have

  • Experience with Azure (or AWS/Google Cloud Platform) AI services, key vaults, and networking.
  • Knowledge of Model Context Protocol (MCP) or tool-server patterns for secure tool access.
  • Experience with retrievers (BM25, hybrid search), re-rankers, or LlamaIndex/LangChain.
  • Familiarity with streaming UIs and structured outputs (JSON, Pydantic schemas).
  • Background in LLM finetuning, RLHF/DPO, or synthetic data generation.
  • Front-end basics for AI UX (React/Next.js) or chat UI patterns.
  • Domain knowledge in HR/ATS, customer support, or internal enterprise workflows.

Work Site: Atlanta, GA (3 days/week onsite)

Duration: 6+ months

Expected Start Date: Immediate - 2 weeks

Number of Positions: 01

Please send your responses back to

About Solution IT

Solution IT is a national IT consulting company specializing in: Technology Staffing and Oracle E-Business Solutions based in Boston, Massachusetts.

Thanks

Recruiting Team

SOLUTION IT INC

Work: / Extn 146 / 139 / 145

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Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10290916
  • Position Id: 2026-12531
  • Posted 7 hours ago
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