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Ai Backend Developer Jobs in Indiana (NOW HIRING)

... backend service design Preferred * Understanding of DevOps principles and experience with tools such as GitHub Actions * Experience working with large language model (LLM) APIs or generative AI ...

... backend service design Preferred * Understanding of DevOps principles and experience with tools such as GitHub Actions * Experience working with large language model (LLM) APIs or generative AI ...

VP, Global Head of Engineering

Francisco, IN · On-site

$169.70K - $218.70K/yr

AI Interface.ai is building the AI infrastructure for financial services - bringing agentic AI and ... Experience with TypeScript, Python, or both at a production scale; comfort across the backend ...

As a Senior Backend & AI Engineer, you will be responsible for the design, development, deployment, and operation of business-critical AI features. Previous experience implementing AI features is a ...

AI-Native at every level From the CEO to day-one hires, everyone builds and ships with generative ... Strong engineering skills in one or more areas: front-end, back-end, full-stack, systems, or ...

Senior Machine Learning Engineer

Union City, IN · On-site +1

$95.20K - $130.70K/yr

Want to work across data, retrieval, modeling, and system design You will partner with ML engineers, backend engineers, and product managers to drive the next generation of Kensho's AI products. Why ...

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Ai Backend Developer information

What are the key skills and qualifications needed to thrive as an AI Backend Developer, and why are they important?

To thrive as an AI Backend Developer, you need strong programming skills (especially in Python or Java), a solid grasp of machine learning concepts, and experience with backend frameworks, supported by a degree in computer science or a related field. Familiarity with cloud platforms (like AWS or Azure), containerization tools (such as Docker), and frameworks like TensorFlow or PyTorch is typically required, along with knowledge of RESTful APIs and databases. Problem-solving abilities, teamwork, and clear communication are essential soft skills that help navigate complex projects and collaborate with cross-functional teams. These technical and interpersonal skills ensure robust, scalable AI solutions are developed and maintained efficiently in a rapidly evolving field.

How does the role of an AI Backend Developer typically interact with data scientists and frontend teams?

As an AI Backend Developer, you will frequently collaborate with data scientists to integrate machine learning models into scalable backend systems. This involves translating prototypes into production-ready APIs, ensuring data pipelines are robust, and optimizing inference performance. You’ll also work closely with frontend teams to define API contracts and ensure that data flows smoothly between the user interface and backend processes. Effective communication and teamwork are essential, as these collaborations help deliver seamless AI-powered features to end users.

What are AI Backend Developers?

AI Backend Developers are software engineers who specialize in building and maintaining the server-side infrastructure that powers artificial intelligence applications. They design APIs, manage databases, and implement algorithms that support machine learning models and AI-driven features. Their work ensures that AI systems are scalable, efficient, and securely integrated with other services. AI Backend Developers often work closely with data scientists and frontend developers to deliver end-to-end AI solutions.

What is the difference between Ai Backend Developer vs Data Engineer?

AspectAi Backend DeveloperData Engineer
Required CredentialsBachelor's in CS, AI, or related fields; knowledge of AI frameworksBachelor's in CS, Data Science, or related fields; expertise in data pipelines
Work EnvironmentDeveloping AI models, integrating AI into backend systemsBuilding and maintaining data infrastructure and pipelines
Employer & Industry UsageTech companies, AI startups, enterprises integrating AIData-driven companies, finance, healthcare, tech firms

While both roles require strong programming skills and familiarity with data processing, Ai Backend Developers focus on integrating AI models into backend systems, whereas Data Engineers specialize in building data pipelines and infrastructure. Both roles are essential in AI-driven projects but serve different functions within the data ecosystem.

What are popular job titles related to Ai Backend Developer jobs in Indiana? For Ai Backend Developer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Ai Backend Developer jobs in Indiana look for? The top searched job categories for Ai Backend Developer jobs in Indiana are:
What cities in Indiana are hiring for Ai Backend Developer jobs? Cities in Indiana with the most Ai Backend Developer job openings:

Senior/Lead Forward Deployed Engineer - US

Parloa

Florence, IN

Other

Posted 17 days ago


Job description

About Parloa

Parloa's mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. 

About the role:

As a Senior/Lead Forward Deployed Engineer (SFDE) at Parloa, you'll be on the front lines of enterprise AI adoption - delivering cutting-edge technology into some of the most complex environments in the world. Your mission: lead end-to-end deployment projects from an engineering perspective - not just implementing what exists, but engineering what's required to make it succeed at enterprise scale.

FDEs are our in-field product engineers. You will build what doesn't yet exist, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. Your work is hands-on and code-first - you'll be building, debugging, and engineering solutions directly in the field. What you ship not only makes deployments succeed, it also defines how customers experience Parloa and shapes what our product becomes.

This is not about maintenance. This is about engineering what makes it work in production, under real-world enterprise constraints, at speed and scale

Areas of ownership:
  • Own deployment engineering projects: Lead the technical execution (incl. product engineering) of Parloa's deployments inside large, complex enterprise environments
  • Design for scale and resilience: Architect deployment solutions that meet enterprise-grade requirements for performance, reliability, and security
  • Engineer solutions where none exist: Build custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements
  • Work across systems & stacks: Operate at the intersection of backend engineering, DevOps, and data engineering to ensure seamless delivery
  • Partner with enterprise teams: Collaborate directly with customer engineering organizations to overcome constraints and deliver measurable outcomes
  • Guide and mentor others: Collaborate with and provide technical guidance to more junior in-field engineers
  • Influence at senior levels: Engage with enterprise architects and senior technical stakeholders, discussing solutions and architectures in depth to ensure alignment and credibility
  • Debug under pressure: Rapidly unblock issues in mission-critical environments and ensure customer success.
  • Shape the product: Act as the feedback loop between the field and our core engineering teams - turning deployment learnings into platform evolution
  • Deliver long-term impact: Work closely with Deployment Strategists to ensure scalable architectures and durable customer value

Our Technology Stack: Python,TypeScript, Node.js, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Who you are:
  • 7+ years of professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact
  • Proven track record of leading deep technical deployments and integrations in large-scale enterprise environments
  • Strong technical depth across backend engineering, infrastructure-as-code, Kubernetes/cloud platforms, APIs, and databases - with proven experience in systems design and the ability to go hands-on in production systems
  • Ability to operate independently in ambiguous, high-responsibility settings, especially when deploying live to enterprise systems
  • A builder's mindset with bias for action, creativity under pressure, and an obsession with making things work in the real world
  • Degree in Computer Science, Engineering, or related technical field
  • Strong plus: Experience building or integrating AI/LLM-powered systems (e.g., embedding agent workflows, vector databases, prompt orchestration)
Our recruiting process:

TA Screen Hiring Manager Call Technical Interview Bar Raiser

Salary ranges include OTE

Why Parloa?

We're at the beginning of a new era in customer experience, one where AI doesn't just respond, but understands, reasons, and takes action. We're building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren't just support tickets; they're defining experiences. We're here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale-and want your work to matter in real, everyday moments-this is where you do it.

At Parloa, ownership isn't a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that's evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We've grown beyond the earliest startup phase, but we've kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we're scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.