Description:
Sycomp is a global IT services and logistics provider with extensive expertise in cloud, data center, endpoint management and security solutions. Sycomp’s diverse team of consultants and engineers deliver on the company’s mission to tackle challenging global IT projects through its state-of-the-art integration and warehouse centers and global technology partnerships.
Headquartered in the heart of Silicon Valley, California, Sycomp has successfully shipped, deployed and managed complex IT projects and supporting assets in more than 150 countries helping its Fortune 500 customers and global partners realize a world without boundaries.
Responsibilities
- Design and build AI pipelines that handle real‑world messiness – long‑form media, unstructured documents, streaming data, multi‑modal inputs – including the chunking, context management, retry logic, and output validation that production systems require.
- Architect autonomous agent systems: tool selection, planning loops, memory strategies, evaluation, and the guardrails that keep them from going off the rails.
- Build on AWS using services like Bedrock, S3, Lambda, Step Functions, SageMaker, OpenSearch, and ECS/EKS – choosing the right primitive for the job rather than forcing one pattern everywhere.
- Make pragmatic decisions about model selection, prompt design, fine‑tuning vs. RAG vs. agentic workflows, and cost/latency/quality tradeoffs.
- Own the data layer: how data is ingested, transformed, stored, indexed, and surfaced to models so that outputs are accurate, traceable, and useful.
- Establish evaluation frameworks and observability so we know whether the system is actually getting better when we change it.Collaborate with engineers and stakeholders to translate fuzzy business problems into technical designs and shipped systems.
Qualifications
- 4+ years of software engineering experience, with at least 2 years building AI/ML systems in production.
- Hands‑on experience with AWS, including Bedrock or equivalent foundation model services, and at least a few of: S3, Lambda, Step Functions, SageMaker, OpenSearch, Dynamo DB, ECS/EKS.
- Demonstrable experience building AI pipelines or agentic systems that handle non‑trivial data shapes – long documents, audio/video, large structured datasets, or streaming inputs.Strong intuition for prompt engineering, context window management, chunking strategies, and output validation (structured outputs, schema enforcement, retries on malformed responses).
- Proficiency in Python; comfortable with at least one frameworks in the LLM ecosystem (LangChain, LlamaIndex, LangGraph, Bedrock Agents, Strands, or similar) – though you should also be willing to drop the framework when it gets in the way.Solid grasp of data engineering fundamentals: how to clean, transform, embed, index, and retrieve data so that what reaches the model is actually useful.
- Experience designing evaluation pipelines for non‑deterministic systems – you know that “it worked when I tested it” is not a quality bar.