DATAECONOMY · 1 month ago
GenAI Engineer
Charlotte, AR
Full-time
Hybrid
Mid Level
3+ years expDATAECONOMY is a fast-growing data & analytics company headquartered in Dublin. They are seeking a skilled AI Engineer to develop and deploy large language models and generative AI systems, focusing on designing and operationalizing models from leading providers and leveraging open-source models.
AnalyticsArtificial Intelligence (AI)Big DataCloud ComputingComputerData GovernanceData ManagementInformation ServicesInformation TechnologySoftware
Responsibilities
Architect, develop, and implement LLM-powered and generative AI solutions utilizing both proprietary and open-source technologies (e.g., GPT-4, Llama 3, Gemini, Claude). Customize and fine-tune models for tasks such as chatbots, summarization, and content classification, evaluating the suitability of LLMs for various business needs
Craft, refine, and test model prompts to achieve targeted outputs. Fine-tune pre-trained LLMs using customized data and apply advanced techniques like instruction tuning or reinforcement learning with human feedback as required
Build and maintain stateful, multi-agent workflows and autonomous AI agents using frameworks like Microsoft AutoGen, LangGraph, LangChain, LlamaIndex, and CrewAI. Develop custom tools that enable seamless API integration and task orchestration
Design and deploy RAG pipelines by integrating vector databases (such as Pinecone, Faiss, or Weaviate) for efficient knowledge retrieval. Utilize tools like RAGAS to ensure high-quality, traceable response generation
Serve LLMs via FastAPI-based endpoints and manage their deployment using Docker containers and orchestration tools like Kubernetes and cloud functions. Implement robust CI/CD pipelines and focus on scalable, reliable, and cost-efficient production environments
Construct data pipelines for ingestion, preprocessing, and controlled versioning of training datasets. Set up automated evaluation systems, including A/B tests and human-in-the-loop feedback, to drive rapid iteration and improvement
Partner with data scientists, software engineers, and product teams to scope and integrate generative AI initiatives. Communicate complex ideas effectively to both technical and non-technical stakeholders
Deploy rigorous monitoring and observability tools to track LLM usage, performance, cost, and hallucination rates. Enforce LLMOps best practices in model management, reproducibility, explainability, and compliance with privacy and security standards
Stay abreast of the latest developments in AI/LLMs and open-source innovations. Contribute to internal knowledge sharing, champion new approaches, and represent the organization at industry or academic events
Qualification
Required
At least 3 years in machine learning engineering, with 1–2 years focused on building and deploying generative AI or LLM-based applications
Proficiency in Python and FastAPI, and experience developing RESTful APIs and microservices
Hands-on familiarity with LLM providers (OpenAI, Anthropic, Google, Meta) and with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or Transformers
Proven ability to fine-tune language models and craft effective prompts tailored to specific applications
Experience creating RAG pipelines with vector databases (e.g., Pinecone, Faiss, Weaviate) and evaluation frameworks like RAGAS
Practical knowledge of containerization (Docker), orchestration (Kubernetes), and cloud deployments (AWS, Azure, GCP)
Solid grasp of CI/CD pipelines and LLMOps practices
Excellent teamwork and communication skills, able to bridge technical and business perspectives effectively
Bachelor's degree in Computer Science, Data Science, or a related discipline (Master's degree preferred)
Preferred
Participation in open-source AI/ML projects, or a strong GitHub profile showcasing relevant contributions or publications
Hands-on experience with advanced agentic frameworks or autonomous agent system design
Knowledge of data governance, security protocols, and compliance standards
Deep expertise in vector similarity search, indexing, and familiarity with document stores (such as MongoDB, PostgreSQL) as well as graph databases
Experience with cloud-native AI services like Azure ML, Cognitive Search, or equivalent platforms for scalable generative AI deployment
Company
DATAECONOMY
Dataeconomy believes that the industry is pivotal, with considerable opportunities in re-imagining business models and scaling business.
201-500 employees
H1B Sponsorship
DATAECONOMY has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (57)
2024 (33)
2023 (68)
2022 (46)
2021 (21)
2020 (10)
Funding
Current Stage
Growth StageLeadership Team
Ravi Kopuri
Co-Founder and CEO
Reginald Mathews
Co-Founder and CTO
Company data provided by crunchbase