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Llm Engineer Remote Jobs in Springfield, MA (NOW HIRING)

Knak Digital

AI Engineer

Becket, MA · Remote

AI Engineer Location: Remote (US only) Must be authorized to work in the US and obtain a Public ... LLM-powered features including copilots, document intelligence, search, summarization, and workflow ...

UnitedHealth Group

Software Engineer

Hartford, CT · Remote

$72K - $130K/yr

If you reside near Hartford, CT , you'll enjoy the flexibility of a hybrid-remote position* as you ... LLM frameworks (e.g., LangChain, LangGraph, or similar) * 2 years of experience integrating AI ...

Revvity

Sr. Tax Manager (REMOTE)

Hartford, CT · On-site +1

$134K - $167K/yr

Revvity | About Us Revvity is a developer and provider of end-to-end solutions designed to help ... MST or JD/LLM preferred. * Strong technical knowledge of U.S. international tax regulations ...

All JobsLlm Engineer JobsLlm Engineer Remote JobsLlm Engineer Remote Jobs in Springfield, MA

Llm Engineer Remote information

See Springfield, MA salary details

$25

$53

$76

How much do llm engineer remote jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for llm engineer remote in Springfield, MA is $53.44, according to ZipRecruiter salary data. Most workers in this role earn between $43.12 and $62.02 per hour, depending on experience, location, and employer.

What is the difference between Llm Engineer Remote vs Data Scientist Remote?

AspectLlm Engineer RemoteData Scientist Remote
Required CredentialsAdvanced degree in CS, ML, or related field; experience with NLP and deep learningDegree in CS, Statistics, or related; experience with data analysis and machine learning
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesData analysis, model development, reporting; across various industries
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, tech, e-commerce, and more

While both roles involve machine learning, Llm Engineers focus on developing large language models and NLP applications, often requiring deep expertise in AI research. Data Scientists analyze data to inform business decisions, with broader industry applications. The roles share some credentials but differ in focus and daily tasks.

What are some typical challenges faced by remote LLM Engineers when collaborating with cross-functional teams?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers to develop and deploy large language models. One common challenge is ensuring clear and consistent communication across different time zones and technical backgrounds, which can sometimes lead to misaligned project goals or delays. To overcome this, many teams rely on detailed documentation, regular virtual meetings, and collaborative project management tools. Building strong relationships remotely and proactively sharing updates can make collaboration smoother and more productive.

What are the key skills and qualifications needed to thrive as an LLM Engineer in a remote role, and why are they important?

To thrive as an LLM Engineer remotely, you need strong expertise in machine learning, natural language processing, and proficiency with programming languages such as Python, often supported by a degree in computer science or related fields. Familiarity with frameworks like PyTorch or TensorFlow, experience with cloud platforms (AWS, GCP), and knowledge of large language model architectures are commonly required. Excellent problem-solving skills, self-motivation, and effective remote communication make candidates stand out. These capabilities are crucial for developing, deploying, and maintaining advanced language models while collaborating efficiently with distributed teams.

What is an LLM Engineer (Remote)?

An LLM Engineer, or Large Language Model Engineer, is a professional who designs, develops, and optimizes applications using advanced AI language models such as GPT-4 or similar technologies. Working remotely, they are responsible for integrating these models into products, fine-tuning them for specific tasks, and ensuring their performance and reliability. LLM Engineers often collaborate with data scientists, software developers, and product managers to create solutions in areas like chatbots, content generation, and natural language processing. Their work requires a strong background in machine learning, programming, and cloud computing.
What are the most commonly searched types of Llm Engineer jobs in Springfield, MA? The most popular types of Llm Engineer jobs in Springfield, MA are:
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What job categories do people searching Llm Engineer Remote jobs in Springfield, MA look for? The top searched job categories for Llm Engineer Remote jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Llm Engineer Remote jobs? Cities near Springfield, MA with the most Llm Engineer Remote job openings:
Llm Engineer Remote jobs near you
Infographic showing various Llm Engineer Remote job openings in Springfield, MA as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $111,162 per year, or $53.4 per hour.

AI Engineer

Knak Digital

Becket, MA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 29 days ago

Job description

AI Engineer Location: Remote (US only)

Must be authorized to work in the US and obtain a Public Trust Clearance.

A small, technical digital services firm working with federal and commercial clients is hiring an AI Engineer to build and ship production-grade applications powered by large language models.

This is a hands-on engineering role. You will design agentic systems, build MCP servers and clients, maintain RAG pipelines, and write the Python backends that expose AI capabilities to real users, including senior government stakeholders. You will also help shape how the organization adopts generative AI responsibly across an active client portfolio.

This is not a research role. No foundation model training. You will be designing and shipping systems that people depend on, and you will have a direct voice in how that gets done.

What you will build:

  • Multi-step agents that plan, call tools, retrieve context, and take action with human-in-the-loop checkpoints
  • MCP servers and clients that securely connect models to client data, internal tools, and APIs
  • RAG pipelines covering chunking, embeddings, vector stores, retrieval, reranking, and grounding
  • LLM-powered features including copilots, document intelligence, search, summarization, and workflow automation
  • Evals and observability so the team knows what is working in production and what is regressing

What you need:

  • 5 or more years of professional software engineering experience, with at least 1 year shipping LLM-based or AI-powered features to production
  • Proficiency in both Python and JavaScript
  • Hands-on experience designing or building agentic systems using tool calling, multi-step reasoning, planning loops, or agent orchestration (LangGraph, CrewAI, OpenAI Agents SDK, Claude tool use, or equivalent)
  • Working knowledge of MCP or demonstrated ability to pick it up quickly
  • Experience building and deploying backend services and APIs (FastAPI, Flask, or similar)
  • Experience with at least one major LLM provider: OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex, or open-weight models
  • Working knowledge of RAG: embeddings, vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar), and retrieval evaluation
  • Comfort with prompt engineering, structured outputs, and tool/function calling
  • Experience writing evals for non-deterministic systems
  • Solid SQL and comfort with relational and unstructured data
  • Familiarity with at least one cloud platform: AWS, Azure, or GCP
  • Strong written communication -- you can explain AI tradeoffs to non-technical stakeholders

Nice to have:

  • Experience authoring MCP servers for non-trivial systems
  • Eval and observability platform experience (Braintrust, LangSmith, Langfuse, Arize, or custom)
  • Multi-agent orchestration and experience reasoning about agent failure modes
  • Fine-tuning, distillation, or LoRA experience
  • Docker, Kubernetes, and CI/CD for AI workloads
  • TypeScript/Node for full-stack AI features
  • Background supporting federal or government clients
  • Awareness of NIST AI RMF, FedRAMP, or related responsible AI frameworks

Requirements:

  • Must be a US citizen or legal resident, able to work domestically
  • Must be able to attain a low-level security clearance

Benefits:

  • Medical insurance (Aetna, Anthem, UnitedHealthcare, Kaiser, and more)
  • Dental insurance (Aetna, Delta Dental, Guardian, MetLife)
  • Vision insurance (Aetna/EyeMed, VSP)
  • Health Savings Account (HSA)
  • Life and AD&D insurance (MetLife)
  • Short-Term and Long-Term Disability (The Hartford)
  • Employee Assistance Program (EAP)
  • Health Advocate
  • Commuter Benefits (HealthEquity)
  • Voluntary benefits (Aflac, MetLife Pet, Legal Services, DIGI, Farmers auto/home)
  • 401K

All interviews will be conducted through video.