AI​/ML Engineer

Company Description Giggso is a Michigan-founded company established in 2017, focused on helping enterprises navigate complex digital transformation initiatives. As a certified Minority Business Enterprise (MBE), Giggso leverages diverse perspectives to solve challenging AI and governance problems. The company partners with Fortune 500 clients worldwide, helping them scale from limited AI pilots to high-impact AI profit centers. Giggso specializes in the intersection of Governance, Risk, Compliance (GRC) and Engineering, turning AI governance from a bottleneck into a strategic advantage.

More information is available at

Required Skills

Programming Expertise:
Strong proficiency in Python (primary), with working knowledge of Java or Go.

Generative AI:
Hands-on experience with LLMs (e.g., GPT, Claude, Llama), prompt engineering, fine-tuning, and multi-agent orchestration.

Data AI:
Proven ability to build and optimize data-driven AI models for analytics, forecasting, anomaly detection, and decision support.

RAG Pipelines:
Experience developing retrieval-augmented generation workflows using vector databases (FAISS, Pinecone, Weaviate).

MLOps Practices:
Familiarity with CI/CD for ML models, monitoring, drift detection, and deployment automation.

Cloud Platforms:
Strong knowledge of AWS, Azure, or GCP for deploying and scaling AI workloads.

API & Microservices:
Ability to design and integrate AI models into enterprise applications via APIs and microservices.

Security & Compliance:
Understanding of responsible AI practices including bias detection, PII handling, guardrails, and auditability.

Collaboration & Communication:
Strong stakeholder management, cross-functional collaboration, and clear communication of technical concepts.

Hands-on with frameworks like Lang Chain, CrewAI, Auto Gen.

Strong in RAG architectures, tool-calling, memory, reflection/critique loops.

Proven delivery of at least one production-grade multi-agent GenAI system.

Python proficiency (preferred language for agentic workflows).

Familiarity with cloud AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex, Anthropic APIs).

Experience designing persona catalogs, system prompts, tone/authority boundaries.

Ability to operationalize persona adaptation within agent flows (not post-processing).

Hands-on RCA in complex systems (network, IT ops, customer journeys).

Embedding RCA methodologies (5 Whys, Ishikawa, fault tree) into agent workflows.

Integration with observability tools (logs, metrics, traces, events).

Knowledge of guardrails, PII handling, access control, auditability, responsible AI practices.

Ability to enforce policy-bound behavior in enterprise contexts.

End-to-end program ownership (design → pilot → hypercare).

Experience in regulated industries (telecom, finance, healthcare).

Strong stakeholder management and ability to present outcomes in business-friendly language.

8–12 years in AI/ML, software engineering, or data science.

2–3+ years specifically in GenAI / agentic systems.

Must have delivered at least one production or late-stage pilot of a multi-agent GenAI system.