Senior AI Engineer

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SysMap Solutions

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

💼 Consulting

📣 Marketing

🤖 Artificial Intelligence

Consulting • Marketing • Artificial Intelligence

SysMap Solutions is a services company devoted to offering technological development to its customers since 1997. With a focus on cloud solutions, Salesforce, mobile development, CRM, user experience, DevOps, machine learning, and digital transformation, SysMap Solutions leverages its extensive experience to craft complex codes and systems that meet client demands. The company prides itself on its ability to deliver tailored solutions, ensuring that the final product is precisely aligned with customer needs. In the Age of Information, SysMap Solutions stands out as a knowledgeable partner in technology.

📋 Description

• Design and implement multi-agent systems with tool orchestration, memory, routing, and fallback mechanisms • Build and optimize RAG pipelines, including ingestion, chunking, indexing, hybrid search, reranking, and retrieval quality evaluation • Develop APIs and services in Python (FastAPI) to expose AI capabilities, including testing, versioning, and CI/CD • Define and implement the evaluation layer with benchmark datasets, quality metrics, prompt regression, and automated tests prior to each release • Instrument LLM observability, including tracing, token usage, cost per request, error rate per tool, and latency per step • Optimize cost and performance through model selection, tuning reasoning effort, caching, batching, and context reduction • Integrate agents with legacy systems and corporate channels, handling authentication, rate limits, idempotency, and reprocessing

🎯 Requirements

• Proven experience in advanced Python development, including typing, async, project structuring, testing, and engineering best practices • Hands-on experience deploying LLM applications to production • Proficiency with agent orchestration frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, or equivalent proprietary SDKs • Practical experience with end-to-end RAG and vector databases/search engines such as Azure AI Search, OpenSearch, pgvector, Qdrant, and Elasticsearch • Strong understanding of applied prompt engineering, structured outputs, function calling, and hallucination mitigation strategies • Experience with at least one public cloud in production, including containers, serverless, messaging, and identity and access management • Familiarity with Docker, Git, and CI/CD pipelines • Ability to communicate technically with clients, including presenting architectural decisions and defending trade-offs • Plus: experience with Amazon Bedrock, Amazon SageMaker, EKS, ECS/Fargate, Lambda, Step Functions, OpenSearch Service, S3, DynamoDB, Aurora PostgreSQL with pgvector, API Gateway, SQS, SNS, EventBridge, IAM, VPC, Secrets Manager, KMS, CloudWatch, and X-Ray

🏖️ Benefits

• Remote work • Role also open to candidates with disabilities