Note: The job is a remote job and is open to candidates in USA. Sycomp is a global IT services and logistics provider specializing in cloud and data center solutions. They are seeking an AI Engineer to design and build AI pipelines and autonomous agent systems on cloud infrastructure, focusing on transforming ambiguous problems into reliable production workloads.

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

Skills

• 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, DynamoDB, 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
• Experience with Azure (Azure OpenAI, AI Foundry, AI Search) or GCP (Vertex AI, Gemini APIs)
• Background in multi-modal systems (vision-language models, audio transcription pipelines, video understanding)
• Experience with vector databases (Pinecone, Weaviate, pgvector, OpenSearch k-NN) and hybrid retrieval strategies
• Familiarity with fine-tuning, distillation, or model adaptation techniques
• Experience with MLOps tooling, model versioning, and A/B testing for AI systems
• Contributions to open source AI/ML projects

Benefits

• A comprehensive benefits package, including health, dental, vision, and other standard benefits

Company Overview

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