Applied AI Engineer

Posted An Hour Ago
Be an Early Applicant
2 Locations
In-Office
Junior
Energy
The Role
Partner with stakeholders to discover AI use cases, configure enterprise GenAI tools, build and maintain high-quality prompts, contexts, and RAG/document-intelligence pipelines, evaluate and improve AI outputs, create reusable playbooks/templates, and enable teams on governed, production-ready AI workflows.
Summary Generated by Built In
We are seeking a talented and detail-oriented Applied AI Engineer to join our Global Data Science team and help internal technology and commercial teams adopt CCI’s approved AI tooling effectively. The ideal candidate will combine technical fluency, strong communication skills, and practical experience using AI to improve real business workflows.
This role will focus on context engineering, AI tooling configuration, assistant and knowledge-base setup, workflow discovery, evaluation, documentation, and stakeholder enablement. The analyst will work hands-on with CCI’s GenAI platform and approved enterprise AI tools to translate business needs into reliable, governed, and reusable AI-enabled solutions.

Responsibilities

  • Partner with traders, analysts, operators, technologists, and business stakeholders to identify workflows where AI can reduce manual effort, improve quality, or accelerate analysis.

  • Configure and support approved AI tools and platform capabilities, including GenAI projects, agents, skills, knowledge bases, SQL resources, model presets, and MCP-enabled tools.

  • Design and maintain high-quality AI context, including system instructions, prompt templates, examples, reference materials, retrieval sources, workflow guardrails, and output formats.

  • Support RAG and document-intelligence workflows, including document ingestion, chunking, metadata design, retrieval quality, structured extraction, and validation with subject-matter experts.

  • Evaluate AI outputs for accuracy, groundedness, completeness, formatting, usability, and business value; use feedback and test cases to improve configurations over time.

  • Create reusable playbooks, templates, demos, and reference materials that help technology and commercial teams use AI safely and effectively.

  • Communicate AI capabilities, limitations, risks, and recommended usage patterns clearly to both technical and non-technical stakeholders.

  • Stay current on practical advancements in applied AI, context engineering, enterprise copilots, agentic workflows, RAG, and AI evaluation methods.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Information Systems, Business Analytics, Economics, Mathematics, or a related technical or quantitative field.

  • 2+ years of experience in data analytics, business analysis, technology enablement, AI implementation, automation, systems configuration, or a related role.

  • Strong practical experience using generative AI tools to improve analysis, documentation, coding, research, workflow automation, or business productivity.

  • Working knowledge of LLM concepts, including prompting, context windows, retrieval, hallucination risk, structured outputs, model selection, and evaluation tradeoffs.

  • Familiarity with applied AI patterns such as RAG, embeddings, vector search, document extraction, tool calling, agentic workflows, and human-in-the-loop review.

  • Strong programming and data skills, including Python, SQL, and tools/libraries used in agentic development like langgraph, langchain, Pydantic models, NumPy, FastAPI/MCP, etc.

  • Ability to work with APIs, JSON, MCPs, Git or version-controlled artifacts, and lightweight automation or prototyping workflows.

  • Excellent written and verbal communication skills, with the ability to translate business needs into technical requirements and explain AI concepts in plain language.

  • Strong problem-solving skills, curiosity, attention to detail, and ability to work independently while collaborating across commercial, technology, and control functions.

  • Understanding of responsible AI and Software practices, including data sensitivity, access control, auditability, and appropriate escalation of higher-risk use cases.

  • Proven ability to work effectively in a fast-paced, dynamic, and high-intensity environment with timely responsiveness and flexibility to work beyond normal business hours when required.

Prefered Qualifications

  • Experience or interest in commodities, energy, trading, logistics, asset operations, market analytics, or commercial decision-support workflows.

  • Hands-on familiarity with enterprise AI tools such as Claude, ChatGPT/OpenAI, Gemini, Microsoft 365 Copilot, Cursor, or GitHub Copilot.

  • Exposure to Snowflake, vector databases, knowledge-base configuration, and cloud platforms such as AWS or Azure.

  • Portfolio examples showing practical AI use: an agent, workflow automation, prompt/context library, RAG prototype, document extraction workflow, evaluation framework, or AI-enabled business process improvement.

Employee Programs & Benefits:

CCI offers competitive benefits and programs to support our employees, their families and local communities. These include:

  • Competitive comprehensive medical, dental, retirement and life insurance benefits

  • Employee assistance & wellness programs

  • Parental and family leave policies

  • CCI in the Community: Each office has a Charity Committee and as a part of this program employees are allocated 2 days annually to volunteer at the selected charities.

  • Charitable contribution match program

  • Tuition assistance & reimbursement

  • Quarterly Innovation & Collaboration Awards

  • Employee discount program, including access to fitness facilities

  • Competitive paid time off

  • Continued learning opportunities

Visit  https://www.cci.com/careers/life-at-cci/# to learn more!

#LI-CD1

Skills Required

  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, Business Analytics, Economics, Mathematics, or related field.
  • 2+ years of experience in data analytics, business analysis, technology enablement, AI implementation, automation, systems configuration, or related role.
  • Practical experience using generative AI tools to improve analysis, documentation, coding, research, workflow automation, or business productivity.
  • Working knowledge of LLM concepts: prompting, context windows, retrieval, hallucination mitigation, structured outputs, model selection, evaluation tradeoffs.
  • Familiarity with applied AI patterns: RAG, embeddings, vector search, document extraction, tool calling, agentic workflows, human-in-the-loop review.
  • Strong programming and data skills, including Python and SQL.
  • Experience with agentic development tools/libraries such as LangGraph, LangChain, Pydantic, NumPy, FastAPI/MCP.
  • Ability to work with APIs, JSON, MCPs, Git, and lightweight automation or prototyping workflows.
  • Excellent written and verbal communication skills; translate business needs into technical requirements.
  • Understanding of responsible AI and software practices: data sensitivity, access control, auditability, escalation for high-risk use cases.
  • Proven ability to work effectively in a fast-paced, dynamic environment with responsiveness and occasional work beyond normal hours.
  • Experience or interest in commodities, energy, trading, logistics, asset operations, market analytics, or commercial decision-support workflows.
  • Hands-on familiarity with enterprise AI tools such as Claude, ChatGPT/OpenAI, Gemini, Microsoft 365 Copilot, Cursor, or GitHub Copilot.
  • Exposure to Snowflake, vector databases, knowledge-base configuration, and cloud platforms such as AWS or Azure.
  • Portfolio examples (agent, workflow automation, prompt/context library, RAG prototype, document extraction workflow, evaluation framework, or AI-enabled business process improvement).
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The Company
HQ: Stamford, CT
573 Employees
Year Founded: 2001

What We Do

Castleton Commodities International is an independent global energy commodity merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets.

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