Haystack Github Jobs Salary Jobs in Usa

Compensation

$170k-$225k

0.17%-1.04%

TLDR

We are growing fast, profitable, and need to hire a Founding Back End Engineer ASAP. This role is focused on selling Neon’s automation platform to healthcare and life sciences organizations, owning the full sales cycle from prospecting through close. Ideal candidates have enterprise SaaS sales experience, thrive in high-growth environments, and are motivated to build a category-defining company. You should have at least 4 years of experience.

Our Market

The crisis: Sarah delayed cancer treatment for weeks facing massive monthly costs. Marcus's autoimmune condition worsened while battling insurance denials.

Over 50% of critical prescriptions are abandoned due to:

• Cost barriers: Patients with high copays are 5x more likely to abandon treatment
• Insurance maze: Complex prior authorizations block access
• Logistical challenges: Coordinating medical visits for treatments

Neon's technology eliminates these obstacles by automating patient access workflows for pharma companies: —automating authorizations, streamlining benefits verification, and unlocking financial assistance.

Why Join?

• Frighteningly ambitious: We’re seasoned builders on a mission to create a $200B+ company—on the scale of Palantir or ServiceNow—serving the largest healthcare enterprises.
• Experienced founding team: Built by exited founders, YC & MIT alum, ex-Tesla, ex-Google engineers.
• Hypergrowth with stability: We went from initial idea to 7+ figure customer contracts in just 4 months—in an industry where sales cycles typically take 12-18 months. We are profitable and relentlessly focused on execution.
• Powerhouse backing: We’re funded by elite Silicon Valley VCs who've backed unicorns like DoorDash, Lyft, and Mammoth Biosciences. And strategic healthcare investors with deep industry connections.
• Outsized impact & opportunity: Work at the intersection of agentic AI, healthcare transformation, and life-changing patient outcomes.

Required Skills

Technical skills:

• Proficiency with Node, Typescript, and Python.
• Good understanding of system design concepts - distributed systems, reliability/performance tradeoffs
• Experience in API design, implementation, and documentation
• Experience using AI coding tools (Cursor, Github Copilot, Claude, etc)
• Experience working with CI/CD systems and good DevOps skills a nice to have
• Excellent documentation and testing habits
• Proficiency with version control (Git)

Soft skills:

• 10x mindset - you’ll be among the first engineering hires!
• You are a fun human!
• Good time management and planning skills

Experience

4-7 years of experience (or equivalent) as a software engineer.

We’re leveling this role to Pave’s “P4” level: Leads project teams, provides direction, and keeps stakeholders informed. Determines key milestones and provides updates and check-ins to relevant teams and partners.

• You are able to work with the rest of the team to:
• 
  
• Define priorities
• Suggest good solutions
• Excel at implementation
• You pick up concepts quickly, pattern match on past problems.
• You are obsessed with speed and quality, and help embed that quality into the rest of the team.
• You are self-directed, and do not need help organizing / prioritizing your time.

Specific project experience

• Nice if you have worked on distributed architectures in the past, but not a strict requirement.
• You must have experience working on projects touching many parts of a large codebase.

Are you an experienced Machine Learning Scientist with a desire to excel? If so, then Talent Software Services may have a job for you! Our client is seeking an experienced Machine Learning Scientist for a contract-to-hire role at their company in South San Francisco, CA.

Position Summary: In the Structure and Simulation team within Prescient Design, we develop modern computational methods to accelerate therapeutic discovery across clients' Research and Early Development (gRED). Methods we deploy propose new molecules, score designs to prioritize the most promising compounds, generate biological hypotheses through exploratory simulation, accelerate physics-based calculations, and more. We are seeking a highly motivated Machine Learning Scientist to join our team to develop new scientific methodology and produce and deploy workflows usable by computational and, ultimately, wet-lab scientists. The successful candidate will collaborate extensively with computational and experimental researchers within Prescient Design and across gRED to advance our scientific understanding of biomolecules.

Primary Responsibilities/Accountabilities:

• Work as a machine learning scientist to develop new scientific methodology for the understanding, scoring, ranking, generation, and design of biomolecules, especially proteins.
• Work as an engineer of scientific software, to produce usable, deployable code for these new methods to power the lab-in-the-loop.
• Use software best practices (version control, testing, modular code development, documentation, etc.) to collaborate on a large codebase with our team of methods developers.
• Deploy workflows on HPC and cloud platforms and deliver user-friendly web-based interfaces to medicinal chemists across gRED and Roche.

Qualifications:

• BS, MS, or PhD degree in a life or physical science or a computational field.
• Expert in Python and experience with scientific software development.
• Experience with deploying software workflows on cloud and/or HPC platforms.
• Experience working on collaborative code bases, including merge requests, code review, writing tests etc.
• Highly motivated and independent self-starter who is eager to collaborate.
• Excellent communication and interpersonal skills.
• Basic understanding of modern machine learning methods, including predictive models, generative models, and active learning, as applied to molecular generation and optimization.

Preferred:

• Candidates may additionally have, but are not required to have:
• Public portfolio of projects available on GitHub.
• Experience with Rosetta, OpenMM, and/or computational chemistry codes.
• 3+ years of industry experience.
• Extensive experience working with large chemical and biological datasets, including graph, sequence, and structure-based data.

6 Month Contract to Hire

Onsite 3 days/week – Hartford, CT

$55/hr-$65/hr

Must‑Have Qualifications

• Strong experience as a full stack developer delivering complex, enterprise‑scale applications
• Hands‑on experience designing and implementing conversational AI solutions using IBM WatsonX Orchestrate or similar platforms (Dialogflow CX, Amazon Lex, , LivePerson)
• Proficiency in NodeJS/TypeScript and Java with Spring, building RESTful web services
• Solid understanding of scalable architecture patterns, data lifecycle management, and cloud‑native development
• Experience developing and deploying microservices on OpenShift or comparable container platforms
• Strong Agile experience, including breaking down user stories into tasks and estimating work within a SAFe delivery model
• Strong collaboration and communication skills across co‑located, cross‑functional teams

Nice‑to‑Have Qualifications

• Experience with Angular, React, HTML, CSS, JSP, or Python
• Familiarity with Speech‑to‑Text tuning and SSML for text‑to‑speech refinement
• Exposure to analytics and data platforms such as Tableau, Alation, DataRobot, or Trifacta
• Experience with CI/CD pipelines using tools such as Jenkins, GitHub, or Octopus
• Strong business acumen and interest in emerging AI and conversational technologies

Day‑to‑Day

In this role, you will design, build, test, and deploy conversational AI solutions that deliver accurate, scalable, and context‑aware chatbot and voice experiences. You will participate in feature and user story refinement sessions, translate requirements into technical implementations, and develop conversational flows that integrate with enterprise APIs, cloud functions, and backend systems. You will collaborate closely with product managers, UI/UX designers, backend engineers, and other developers to ensure seamless end‑to‑end delivery. On a daily basis, you will troubleshoot, debug, tune, and optimize conversational agents across multiple channels, apply clean coding standards, and continuously improve conversational accuracy using NLP and training data best practices.

Our Ideal Candidate

We are seeking an experienced cloud and DevOps engineer with over 5 years of experience designing, automating, and maintaining scalable AWS infrastructure, CI/CD pipelines, and secure cloud environments. In the role of Senior Cloud Platform Engineer, you should demonstrate expertise in Infrastructure as Code, scripting, containerization, and modern monitoring or alerting platforms, as well as strong skills working across teams. Success in this position requires a talent for optimizing cloud resources, ensuring security and compliance, and facilitating fast, reliable software deployments. Having experience with HIPAA-compliant systems, .NET platforms, or serverless computing is considered a significant advantage.

Responsibilities

• Design, implement, and maintain CI/CD pipelines using tools like AWS CDK, AWS CodePipeline, or GitHub Actions.
• Manage infrastructure as code (IaC) using Terraform, CloudFormation, or similar tools.
• Monitor system performance and availability using tools like CloudWatch, Prometheus, Grafana, or Datadog.
• Automate repetitive tasks and deployment processes to improve team efficiency.
• Collaborate with software engineers, QA, and product teams to ensure smooth deployments and rapid iteration.
• Implement and enforce security best practices and compliance across infrastructure and deployment pipelines.
• Identify optimizations to reduce cloud resource usage across AWS accounts.
• Maintain documentation for infrastructure, processes, and compliance requirements.
• Work with multiple teams to implement their deployments using common practices.
• Manage Builds and the corresponding documentation
• Monitor package versions, track EOL dates, and upgrade to keep infrastructure current

Qualifications

• B.S. Computer Science degree or equivalent experience.
• 5+ years of experience in DevOps, Site Reliability Engineering, or related roles.
• 2+ years of hands-on AWS Experience
• Strong experience with cloud platforms (AWS, Azure, or GCP).
• Proficiency in scripting languages such as Bash, Python, or PowerShell.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with monitoring, logging, and alerting tools.
• Solid understanding of networking, security, and system administration.
• Strong communication skills and ability to work cross-functionally.

Propy is revolutionizing the real estate industry by building the world's first AI-powered Title and Escrow platform onchain. We have processed over $5B in transactions, and we are on a mission to make closing on a home as easy as buying a stock.

We combine blockchain for security with advanced AI to automate the heavy lifting of closing documents. We aren't just "using" AI; we are building the infrastructure that allows AI agents to securely manage escrow, eliminate fraud, and run 24/7.

We are looking for a pragmatic Applied AI Engineer to join our engineering team.

The role is not about training models and does not involve academic Machine Learning research. It is about building the rails that make AI usable in a high-stakes financial environment. You will bridge the gap between our robust C#/.NET architecture and the probabilistic world of LLMs.

Title and Escrow is a document-heavy industry with zero room for error. Your mission is to use AI to clean up the messiness of real-world real estate data.

You will solve problems like:

• Structured Data Extraction: Converting messy, unstructured data (like emails, PDFs, documents)  from various sources into strictly validated JSON schemas with as close to 100% accuracy as possible.
• Escrow Automation: Designing workflows that reduce human intervention by 50% by intelligently routing tasks based on AI analysis.
• Fraud Detection: Implementing deterministic logic checks on bank and financial documents to detect fraud patterns before they happen.

• Engineer the Integration: Writing production-grade code that interacts with external AI APIs
• "Prompt Engineering" as Code: You won't just write prompts; you will version, test, and optimize them. You will define strict schemas to ensure the AI speaks the language of our internal tools.
• Orchestrate & Validate: Help in building the logic that parses AI responses, validates them against our database (MongoDB), and flags inconsistencies before they reach the user.
• Full-Stack Implementation: Work to visualize AI-aided services and data for user review and approval.
• Collaborate: Work closely with the other senior engineers and product owners to translate complex "Title & Escrow" schemas into technical constraints that an AI can understand.

• Developer DNA: You are a software engineer first. You have strong experience in Python (C# / .NET is an advantage) and understand programming in depth. 
• Applied AI Experience: You have integrated LLMs into applications via API. Have experience with not only models but also AI frameworks. Experience with workflows, AI agent building and orchestration. You understand context windows, token limits, temperature, and guardrails.
• Data Handling: Experience with handling complex data structures.
• The "Glue" Mindset: You enjoy writing the code that connects different services ( like the AWS, AI APIs, and Database) to make a seamless features.
• Collaborative Autonomy: You will own the AI domain, but you won't be on an island. You will be embedded in a senior engineering team that supports you with architecture, code reviews, and best practices.

• Experience with AWS infrastructure.
• Familiarity with the US Real Estate, Title, or Escrow process.

• Working in a transparent environment which focuses on solving problems and getting things done.
• The opportunity to work with very smart and driven people.
• The ability to grow your talents and career in a high-growth sector.
• A remuneration package that is based on the candidate's motivation, skills, and experience.

Please submit your resume to this job ad along with a portfolio of your AI-related experience, GitHub account and anything else you find applicable. 

About This Role

This isn't a traditional engineering role where you'll receive detailed specifications and build to order. We're looking for someone who digs into problems firsthand—someone who asks "why" until they truly understand what's broken, then builds the solution themselves.

If you've ever been frustrated by the gap between people who understand the customer and people who can build technology, this role exists because we share that frustration. We want someone who can do both.

What You'll Do

You'll use AI tools—particularly Claude Code and the Claude platform—to build solutions that solve real problems in mortgage lending. Not proofs of concept. Real tools that people use every day.

Examples of problems you might tackle:

• Loan conditions arrive from Fannie Mae, Freddie Mac, VA, and FHA in different formats. Loan officers spend hours reconciling them. Build something that consolidates and deduplicates them automatically.
• Underwriters spend significant time on tasks that could be automated, but "that's how it's always been done." Identify which tasks, understand why, and build the automation.
• Compliance requirements evolve constantly. Build systems that can adapt without requiring lengthy development cycles.

You won't always be handed a clear spec. You'll often be handed a problem—sometimes a vague one—and expected to dig in until you understand it well enough to solve it.

What We're Looking For

Required:

• You can build working software. You don't need a team of engineers to ship something useful. Claude Code, Python, JavaScript, APIs—you're comfortable getting hands-on.
• You go deep on problems. When someone says "we need a dashboard," you ask what decision they're trying to make. When they say "it takes too long," you ask how long, why, and what happens as a result.
• You're persistent. You don't hear "that's not possible" and stop there. You get curious and look for another way.
• You communicate well across audiences. Executives, loan officers, underwriters, compliance teams—you can work with all of them effectively.

Preferred:

• Bachelor's degree in Business, Computer Science, or related field
• Experience in mortgage lending, financial services, or another regulated industry
• Hands-on experience with AI coding tools (Claude Code, Copilot, Cursor, or similar)
• Background that spans both business and technical work—perhaps you started in analysis and taught yourself to code, or you're an engineer who consistently finds yourself thinking about the customer problem

What matters most:

We care less about your pedigree and more about your ability to solve problems and work well with others while doing it.

Why This Role Exists

We're a 200-person mortgage lending organization, and we believe AI is going to fundamentally change how our industry operates—not by replacing people, but by making our people dramatically more effective.

We're moving away from the traditional model where business teams write requirements, hand them to engineers, and hope the result matches the intent. We want to build a team of people who can understand the problem deeply and build the solution directly. Fewer handoffs. Faster iteration. Better outcomes.

If that resonates with you, we'd like to talk.

How To Apply

Please send:

1. Your resume
2. Something you've built — a link, screenshot, GitHub repo, or brief walkthrough. It doesn't need to be polished. We want to see how you approach problems.
3. A short note (a few sentences) about a problem you investigated deeply and what you learned from it

Role: Java Solution engineer Architect

Skills: Core Java, Azure (Public Cloud), AI-assisted development tools (GitHub Copilot, etc.)

Experience: 15 + Years

Location: Chicago

We are seeking a highly skilled and experienced Java Solution engineer Architect who brings more than traditional development capability—someone with a core engineering mindset, strong independent problem‑solving skills, and the ability to influence and uplevel an existing team. This role is central to our transformation journey to modernize legacy systems and move toward an autopilot engineering model. The ideal candidate is not an “order-taker” but a Better Engineer—someone who can diagnose issues, architect solutions, and drive modernization without needing step-by-step direction.

Job Description:

Tech Stack: Core Java, Azure (Public Cloud), AI-assisted development tools (GitHub Copilot, etc.)

Transformation & Coaching

• Assessment & Roadmap Creation:
• Evaluate the current technology landscape, identify gaps, and shape the transformation roadmap for modernization.
• Culture Change Agent:
• Break entrenched “comfort zone” patterns across a team with 10+ year legacy experience.
• Mentor team members and interns on modern engineering practices, automation-first thinking, and cloud-native principles.
• AI Adoption Leader:
• Promote and operationalize the use of GitHub Copilot and other AI tools for:
• Unit test generation
• Code reviews & optimization
• Issue impact diagnosis
• Development efficiency

Technical Leadership & Delivery

• Self-Sufficient Execution:
• Build systems independently without needing detailed “how-to” instructions. Should naturally handle engineering essentials such as timeouts, retries, dead letter queues, error handling, and resiliency patterns.
• Hands-on Development:
• Write high‑quality Java code while enhancing CI/CD pipelines, improving automated testing, and increasing code coverage.
• Cloud & Infrastructure Ownership:
• Drive Azure-related engineering tasks including IAM, horizontal/vertical scaling, monitoring, and Infrastructure-as-Code (Terraform).
• Operate with a philosophy of application teams owning their infrastructure.

Operational Excellence

• Documentation & Knowledge Sharing:
• Transition knowledge from individuals to scalable, documented, and automated processes; establish best practices and engineering playbooks.
• Resiliency & Scalability Engineering:
• Architect broadly stable systems that minimize production issues and increase platform reliability.