1 день назад
Senior AI Engineer
175 000 - 215 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior AI Engineer (LLM/RAG): Building production AI features for financial services users, including natural-language data transformations, integration suggestions, data quality detection, and automated validation with an accent on LLM pipelines, RAG systems, and agentic workflows. Focus on optimizing accuracy, latency, and cost, building evaluation frameworks, and integrating AI outputs reliably into platform APIs and execution workflows.
Location: Boston, Massachusetts, United States
Salary: $175,000–$215,000 annual base salary plus annual target bonus; ranges are listed for Massachusetts, New York, and New Jersey.
Company
is a global financial services firm providing investor services, capital partnerships, specialist expertise, and technology solutions.
What you will do
- Build production AI features for natural-language data transformation generation, integration configuration suggestions, data quality detection, and automated validation.
- Design and iterate on robust, observable LLM pipelines for financial services data schemas.
- Develop RAG systems and multi-step agentic workflows using Agno, with error handling, retry logic, and human escalation paths.
- Create evaluation datasets and automated scoring frameworks to continuously improve AI output quality.
- Optimize AI systems for accuracy, latency, and cost across different usage patterns.
- Collaborate with Backend Engineers to integrate AI capabilities into platform APIs, workflow layers, and execution services.
Requirements
- 5+ years of software engineering experience and 1+ year focused on production GenAI or LLM applications.
- Experience shipping AI features to real users rather than only prototypes or internal demos.
- Production experience with Anthropic Claude and/or OpenAI APIs, as well as RAG systems.
- Experience with agentic frameworks such as Agno, LangChain, LlamaIndex, or comparable tools.
- Strong Python proficiency, Azure or AWS experience, and knowledge of vector databases such as Pinecone, Weaviate, or pgvector.
- Active daily use of AI coding assistants.
Nice to have
- Financial services or data domain experience, including financial data schemas, transformation logic, or data quality requirements.
- Experience with Temporal or other workflow orchestration systems.
- Experience fine-tuning models or working with open-source LLMs for domain-specific tasks.
- Open-source AI contributions, technical writing, or familiarity with ETL/ELT patterns.
Culture & Benefits
- Partnership-oriented environment with collaborative debate and knowledge sharing.
- Mentoring and guidance from experienced leaders.
- Benefits covering long-term savings, healthcare, income protection, professional development, and time off.
- Opportunities to contribute beyond the immediate role and participate in a diverse professional community.
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