Saviance
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.
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.