Dedicated engineering · Data, cloud & quality
Hire AI engineers
Turn an AI use case into an evaluated feature inside your application. Salt helps US companies add engineering capacity from Pune, India. Define the role, review the fit, and agree how the engineer will contribute to your team.
Salt project experience
Relevant work to explore.
Healthcare & behavioral health
AI-assisted clinical intake
Salt’s clinical intake application connects transcripts and AI-assisted summaries for clinician review, using Amazon Bedrock in its stack.
Read the project storyThis is company project experience. Discuss the proposed engineer’s own contribution and background during selection.
Where the role contributes
Put the expertise to work.
Use these responsibilities to shape your brief. The final scope should reflect your application and the engineer’s assessed experience.
Document processing and structured outputs
Model APIs and retrieval where relevant
Assistants using approved knowledge
Evaluation datasets and failure analysis
AI evaluation and application integration
Permissions, review workflows, and usage monitoring
A practical starting scope
What could this role take on?
An illustrative brief to help plan your engagement; the agreed assignment depends on your application.
Example assignment
A document assistant that returns structured information and routes uncertain results to a reviewer.
A useful first deliverable
An evaluated feature with representative test cases, documented failure behavior, access controls, and a review path.
Define the fit
Start with your system,
not just a job title.
Define the task, available data, review responsibility, and acceptable failure behavior. Distinguish application-focused AI engineering from custom model research or training.
Ask candidates to describe how they would test unsupported answers, missing information, and access restrictions. A compelling demonstration is only one part of production readiness.
Explore ai & automationChoose the responsibility you need
One role—or a coordinated team.
Dedicated AI engineers
A fit when your team already owns product priorities, technical direction, and day-to-day delivery. Define the engineer’s allocation, review process, and interfaces with the rest of your team.
Explore dedicated developersManaged development team
A fit when an agreed workstream needs coordinated engineering, technical leadership, and testing. The proposal defines Salt’s delivery responsibilities and the decisions your business retains.
Explore managed teamsWorking with US companies
Your business in the US.
Engineering with Salt in Pune.
Choose who will lead delivery, then define the working arrangements. The operating model below separates your responsibilities from Salt’s; commercial terms are specific to your engagement.
| Responsibility | Dedicated engineers | Managed development team |
|---|---|---|
| Business priorities | Your product owner sets priorities and accepts business outcomes. | Your product owner sets priorities and accepts business outcomes. |
| Day-to-day delivery | Your team directs the engineer’s tasks, reviews, and delivery process. | Salt coordinates the agreed workstream and reports progress to your decision owner. |
| Technical leadership & QA | Your team supplies leadership and testing unless separately included. | The proposal identifies the leadership and testing included in Salt’s scope. |
| Changes and blockers | Your delivery lead manages prioritization and dependencies. | Salt raises delivery blockers and scope changes for your decision. |
Contracting and billing
Your proposal and agreement need to identify the legal contracting entity, scope, billing currency, payment schedule, and change process. US presence does not by itself determine the entity signing your contract.
Communication overlap
Identify your time zone, essential live meetings, delivery contacts, and escalation owner. Record the overlap window in both US local time and India time, including how daylight-saving changes are handled. Full US-day or 24/7 coverage is not a default commitment.
Source code and access
Separate repository access from legal ownership. Specify who administers the repository and deployment accounts, what code and assets are delivered, any pre-existing or third-party components, and the applicable IP terms.
Progress and acceptance
Define a review cadence, a shared view of work and blockers, and the person authorized to accept a deliverable. For each release, identify the acceptance criteria, known limitations, and unresolved issues.
Handover
List the handover deliverables: source access, setup and deployment instructions, environment requirements, outstanding issues, and a walkthrough. Identify the people receiving access and the system owner after delivery.
Support after delivery
Distinguish defect correction from new features and ongoing operations. Specify the support period, coverage hours, severity definitions, response targets, and escalation route. An ongoing support arrangement must be included explicitly.
From requirement to onboarding
A clear process for building your team.
Define the role
Share your stack, backlog, expected ownership, collaboration hours, and target start.
Review the fit
Discuss suitable profiles and relevant experience. Agree on interviews and any assessment before selection.
Agree & onboard
Confirm allocation, commercial terms, access, working practices, and an initial set of tasks.
Hiring questions
Clarity before
the commitment.
Choose an AI application engineer for integrating model APIs, approved knowledge, evaluation, and review workflows. Training a new model or developing a novel learning approach is a different scope and needs separate expertise, data, and evaluation planning.
Define the task, available data, review responsibility, and acceptable failure behavior. Distinguish application-focused AI engineering from custom model research or training.
Ask candidates to describe how they would test unsupported answers, missing information, and access restrictions. A compelling demonstration is only one part of production readiness.
Availability depends on the required skills, seniority, workload, and selection process. Share your target date so we can discuss a realistic start. A confirmed profile and agreed onboarding plan should come before a delivery commitment.
Pricing depends on the role, experience, allocation, engagement duration, and delivery responsibilities. We scope these with you before providing a proposal. Clarify whether technical leadership, testing, infrastructure, and support are included or supplied by your team.
Include profile review and a role-relevant technical conversation in the selection process. Agree on the assessment format, access to work examples, and who makes the final selection. Any trial period, replacement terms, and notice periods must be stated in the agreement.
In a dedicated engagement, your team directs priorities and day-to-day work. Agree on repository access, code review, intellectual-property terms, confidentiality, and handover in the contract. If you need Salt to coordinate delivery, discuss a managed team instead.
Share the hours when collaboration is essential. Meeting overlap, response expectations, holidays, and any support coverage are agreed for the engagement; a full US working day or 24/7 availability should not be assumed.
Plan your team
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Give your developers focused testing support and clearer release evidence.
Explore roleYour delivery process stays yours.
Dedicated engineers work within your team’s priorities and practices. For Salt-managed delivery, explore SPARK to understand how we structure scope, review, release, and improvement.
How Salt structures deliveryBuild your team with Salt
Tell us where you need AI engineers.
Define the task, available data, review responsibility, and acceptable failure behavior. Distinguish application-focused AI engineering from custom model research or training.