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Generative AI Engineer (Data/ML/GenAI)
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Job Summary:
DATAECONOMY is seeking a Generative AI Engineer with extensive experience in Data, Machine Learning, and Generative AI to design and productionize LLM-powered systems. The role involves selecting and fine-tuning models, crafting workflows, and ensuring the deployment of secure, observable services while maintaining MLOps rigor.
Responsibilities:
Own E2E design for chat/agents, structured generation, summarization/classification, and workflow automation. Choose the right model vs. non-LLM alternatives and justify trade-offs.
Build prompt stacks (system/task/tool), synthetic data pipelines, and fine-tune or LoRA adapters; apply instruction tuning/RLHF where warranted.
Implement multi-agent/tool-calling workflows using AutoGen, LangGraph, CrewAI (state management, retries, tool safety, fallbacks, grounding).
Stand up retrieval stacks with vector DBs (Pinecone/Faiss/Weaviate/pgvector), chunking and citation strategies, reranking, and caching; enforce traceability.
Ship FastAPI services, containerize (Docker), orchestrate (Kubernetes/Cloud Run), wire CI/CD and IaC; design SLAs/SLOs for reliability and cost.
Instrument evals (unit/regression/AB), add tracing and metrics (Langfuse, LangSmith, OpenTelemetry), and manage model/version registries (MLflow/W&B).
Implement guardrails (prompt injection/PII/toxicity), policy filters (Bedrock Guardrails/Azure AI Content Safety/OpenAI Moderation), access controls, and compliance logging.
Build/maintain data ingestion, cleansing, and labeling workflows for model/retrieval corpora; ensure schema/version governance.
Optimize with batching, streaming, JSON-schema/function calling, tool-use, speculative decoding/KV caching, and token budgets.
Partner with product/engineering/DS; review designs/PRs, mentor juniors, and drive best practices/playbooks.
Qualifications:
Required:
6+ years across Data/ML/GenAI
12+ years designing and shipping LLM or GenAI apps to production
Strong Python and FastAPI
Proven experience building secure, reliable REST services and integrations
Hands-on with OpenAI/Anthropic/Gemini/Llama families
At least two of: AutoGen, LangGraph, CrewAI, LangChain, LlamaIndex, Transformers
Practical experience implementing vector search and reranking
Experience with offline/online evals (e.g., RAGAS, promptfoo, custom harnesses)
Docker, Kubernetes (or managed equivalents), and one major cloud (AWS/Azure/GCP)
CI/CD and secrets management
Familiarity with tracing/metrics tools (e.g., Langfuse, LangSmith, OpenTelemetry)
Working knowledge of data privacy, PII handling, content safety, and policy/controls for enterprise deployments
Clear technical writing and cross-functional collaboration
Ability to translate business goals into architecture and milestones
Preferred:
Deeper experience with multi-agent planning/execution, tool catalogs, and failure-mode design
Experience with pgvector/Elasticsearch/OpenSearch
Comfort with relational/NoSQL/graph stores
Human-in-the-loop pipelines, golden sets, regression suites, and cost/quality dashboards
Company:
Dataeconomy believes that the industry is pivotal, with considerable opportunities in re-imagining business models and scaling business. Founded in 2018, headquartered in Ohio, Illinois, USA, team size 201-500 employees, currently Growth Stage. DATAECONOMY has a track record of offering H1B sponsorships.
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Industries
Software Development
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Medical insurance
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401(k)
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