Senior Software Engineer - AI & Data EngineeringSaviance • Boston, MA, United States

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Senior Software Engineer - AI & Data Engineering

Saviance • Boston, MA, United States

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Senior Software Engineer - AI & Data Engineering

Location : Boston, MA (Onsite every Thursday)

About BigRio

BigRio is a Boston-based technology consulting firm specializing in AI / ML, data engineering, custom software development, and digital transformation, with a strong focus on the healthcare and life sciences domains. We partner with leading organizations to deliver cutting-edge, secure, and scalable solutions that drive innovation, improve efficiency, and create measurable business impact. Our team brings deep expertise in emerging technologies such as Generative AI, cloud platforms, and data-driven automation, helping clients transform their operations while ensuring compliance with industry regulations.

Role Overview

We are seeking a highly skilled Senior Software Engineer with strong expertise in AI and Data Engineering. This position emphasizes hands-on technical execution, contributions to team success, cross-functional collaboration, and mentorship, with a strong focus on Generative AI, LLM integrations, and AI-enhanced workflows.

Responsibilities

50% - Technical Execution

Contribute to clear and precise technical design specifications, focusing on GenAI system integration and AI-driven workflows.
Deliver high-quality AI-powered components and services while ensuring security, performance, scalability, and automation best practices.
Estimate development tasks in story points, factoring in LLM inference latency and API rate limits.
Adhere to coding conventions, architectures, and best practices for GenAI applications, prompt engineering, and RAG models.
Write, debug, and deploy production-ready code, ensuring quick fixes for GenAI APIs, embeddings, and microservices.
Integrate and optimize tools / frameworks such as OpenAI, Azure OpenAI, Hugging Face, LangChain, and LlamaIndex .
Utilize vector databases ( Pinecone, FAISS, ChromaDB ) for similarity search and retrieval pipelines.
Meet sprint "Definition of Done (DOD)" including :
Unit and functional testing
LLM benchmarking (BLEU, ROUGE, cosine similarity)
Model validation & API optimization (temperature, top-k, tokens)
Code reviews, bug fixes, and documentation
Responsible AI & governance compliance

30% - Team Contributions

Learn domain-specific AI applications in automation, search, and decision support.

Own AI-driven product features with ongoing model improvement and fine-tuning.

Actively engage in agile ceremonies with an AI-first mindset.

Volunteer for GenAI-related backlog items, such as :

RAG model refinement

Prompt engineering enhancements

LLM evaluation and response tuning

Participate in scrum (stand-ups, sprint planning, retrospectives) with focus on iterative AI model scaling.

Promote self-organization and effective GenAI adoption across teams.

10% - Cross-Functional Collaboration

Work closely with Technology, Product, AI / ML, and DevOps teams to align AI solutions with business outcomes.

Partner with AI engineers, data scientists, and cloud architects to optimize LLM-based solutions.

Ensure compliance with AI governance, privacy, HIPAA, GDPR, SOC2, and ethical AI standards .

10% - Mentorship & Knowledge Sharing

Train and mentor developers on GenAI integration, API usage, embeddings, and vector search.

Guide team members in prompt engineering, RAG optimizations, and API latency improvements .

Encourage use of AI-powered developer workflows (Copilot, AI-driven testing, code generation).

Education, Experience & Skills

5-10 years in engineering roles with exposure to AI / ML.

Bachelor's degree (or equivalent) in Computer Science, Engineering, or related field.

Strong background in software engineering with AI / GenAI model integration .

Proficiency in Python (preferred for AI work).

Familiarity with Unix / Linux, Big Data, SQL, NoSQL, and AI pipelines.

Hands-on experience with OpenAI GPT, Hugging Face Transformers, LangChain, LlamaIndex .

Exposure to RAG models, embeddings, similarity search, and vector databases (FAISS, Pinecone, ChromaDB) .

Experience deploying AI solutions on AWS or Azure OpenAI .

Strong knowledge of AI evaluation metrics (BLEU, ROUGE, BERT Score, cosine similarity).

Agile environment experience preferred.

Behaviors & Abilities

Strong ability to design and implement AI-powered solutions that enhance software functionality.

Analytical problem-solver skilled in debugging and optimizing AI-generated responses.

Collaborative mindset to work across engineering, DevOps, and AI / ML functions.

Deep knowledge of AI-driven feature development, prompt engineering, and embedding optimizations .

Capable of evaluating AI outputs for bias, accuracy, and compliance .

Curious, eager to explore new AI models, frameworks, and best practices for scalable GenAI deployment.

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