Direct Client Req : Gen AI Engineer/Developer @ Reston, VA (Need Locals Only)Please send me your updated resume with below details to
pr...@idexcel.comMust need below details with resume:LinkedIn Profile Link:
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Master’s degree (Subject) with Completion year & University (OR) Educational Institute Name/Location:
Bachelor’s degree (Subject) with Completion year & University (OR) Educational Institute Name/Location:
Job Level: Gen AI Engineer/Developer
Location: Reston, VA (Need Locals Only)
Duration: Long TermExperience Required:
• 8+ years overall in Software Engineering disciplines, preferably in the contracts and legal domain.
• 2-3 years of experience in AI/ML engineering roles
• Strong programming skills in Python, SQL and experience with AWS.
Key Responsibilities:
• Design, test, and refine prompts for large language models (LLMs) to support financial reporting, summarization, and client communication tools.
• Analyze structured and unstructured financial data using Python and SQL, delivering insights through dashboards and reports.
• Develop and maintain data pipelines and ETL workflows to support GenAI model training and evaluation.
• Use AWS SageMaker to build, train, and deploy machine learning and GenAI models.
• Collaborate with data scientists, analysts, and business stakeholders to align AI solutions with financial objectives.
• Monitor model performance and iterate on prompt and model design to improve accuracy and relevance.
• Document workflows, models, and prompt strategies for internal knowledge sharing and compliance.
Required Qualifications:
• 2–3 years of experience in data analysis or machine learning roles.
• Proficiency in Python and SQL for data manipulation and analysis.
• Hands-on experience with major AWS services, particularly SageMaker, S3, Redshift, and Lambda.
• Experience working with LLMs (Anthropic Claude, Sonnet) and prompt engineering techniques.
• Strong understanding of financial data, KPIs, and reporting standards.
• Excellent communication and collaboration skills.
Preferred Qualifications:
• Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG).
• Exposure to data visualization tools (e.g., Power BI, Tableau).
• Understanding of MLOps practices and model lifecycle management.