AI Backend Integration Specialist Needed

@rajat07me

With a decade in the digital industry behind us, my team at 360 Elevate specializes in AI integration, backend development, and the vagaries of JavaScript proficiency. Besides our ability to adopt new technology quickly, our forte lies in building strong digital foundations that meet long-term goals. Our past work with AI automation, CRM-documented workflows, and platform-specific AI systems makes us uniquely qualified for your project. We don't just build chatbots or scattered ML models; we construct flexible products around them. We have experience with TypeScript/serverless backends — exactly what you're on the lookout for. Rather than starting from scratch, our approach is to first audit and preserve what works well in your existing codebase while improving on its weaknesses. This method maximizes efficiency without compromising quality, all within a thoroughly evaluated and proofed framework. What further distinguishes us is our discipline when it comes to delivery - we don't cut corners. With 60+ professionals backed by structured quality control measures ensuring reliable work at scale, we commit to providing precisely what you need: A dependable and measurable product system driven by ground-breaking LLM frameworks. Together, let's solidify your application as an unparalleled consumer software product that delivers on every front.

@Microlent

Reliable AI products are not built by adding prompts around an LLM. The critical work is defining clear boundaries between probabilistic AI behaviour and deterministic backend state, then making the entire system measurable, testable and observable. Your requirement aligns well with how I approach production AI systems. I can audit the existing TypeScript/serverless architecture, preserve reusable components, identify weak points, and complete the AI/backend layer against the V1.5 specification and acceptance criteria. My approach would cover: • Architecture and codebase audit before unnecessary rewrites • Canonical state and AI/tool boundary review • Grounded RAG and evidence-aware retrieval pipelines • Structured outputs with schema validation • Provider/model abstraction and fallback strategies • Queue, webhook and idempotency handling I particularly agree with your principle that AI should extract, reason, rank and suggest, while durable truth and irreversible state remain controlled by deterministic backend services. I can work hands-on with TypeScript, serverless architectures, LLM integrations, RAG pipelines, structured outputs and production testing. I am also comfortable working efficiently with coding agents while maintaining architectural control and code quality. Portfolio: https://www.freelancer.com/portfolio-items/11539740-microlent-systems-portfolio Available to start with the architecture/codebase audit. Jenifer

@diektech

Hi — Elias here from Miami. I understand you're looking for an AI Backend Integration Specialist to enhance your systems with AI capabilities. This project likely aims to streamline workflows and improve user experiences through effective backend integration. What usually matters most here is the complexity of integrating AI models with your current architecture. A common issue in systems like this is ensuring the AI components can scale efficiently while maintaining performance. The tricky part is managing data flow and permissions across different user roles for secure operations. My approach would focus on designing a modular architecture that allows for scalability and easy updates. I’d prioritize clear API structures and robust error handling to ensure reliability as your system grows. I’ve successfully implemented similar integrations in past projects, optimizing workflows and enhancing overall performance. A few questions to better understand the scope: Q1 – What specific user roles and permissions need to be defined for the AI features? Q2 – Are there existing backend systems or APIs that the AI models need to integrate with? Q3 – What are your expectations regarding scalability and future enhancements? Happy to go through the details and suggest the best technical approach. Looking forward to hearing from you.

@OutsourceMan

Yes, at CnEl India, we can take ownership of your AI intelligence and backend integration layer, making your LLM/RAG workflows grounded, testable, and production-ready. Our Technical Execution Methodology System Audit & State Decoupling: Audit your TypeScript/serverless codebase to enforce strict boundaries between AI reasoning and canonical database state, ensuring idempotent queue/webhook execution, role permissions, and data integrity. Grounded RAG & Structured Outputs: Upgrade vector retrieval/reranking pipelines with strict JSON schema enforcement (Zod/Pydantic), provider abstractions (OpenAI, Anthropic), and guardrails to eliminate hallucinations. Automated Evals & Observability: Implement a repeatable evaluation suite (using frameworks like Ragas/DeepEval) to benchmark accuracy and latency against your V1.5 spec, alongside telemetry/logging for full observability. API Integration & Handoff: Expose clean, strongly typed REST/GraphQL endpoints for your frontend team, backed by comprehensive setup docs and CI/CD pipelines. We can start immediately upon review! Best regards, CnEl India Team

@ahmadayaz

With expertise in AI systems and backend engineering for LLM, RAG, evaluations, and TypeScript, I specialize in optimizing consumer software products. By enhancing existing AI layers and backend integrations, I aim to create dependable and efficient systems. My focus includes structured outputs, document ingestion, search functionalities, and AI workflows for a seamless user experience. Let's discuss how we can enhance your AI-backend system for improved user interaction and operational efficiency.

@techplusintl

Hi, I can enhance the AI/backend integration layer of your existing consumer software product to ensure it is reliable and grounded. To achieve this, I will conduct a thorough audit of the current AI/backend implementation. I will identify strengths to preserve and weaknesses to improve, ensuring that the AI layer functions as a dependable product system. I will focus on structured outputs, retrieval mechanisms, and the integration of external execution while maintaining the integrity of the backend software. I will utilize TypeScript and serverless architecture effectively, ensuring that the AI workflows are robust and measurable. Testing will be a priority, and I will establish a repeatable evaluation system to verify the product's behavior. To get started, I will need access to the existing codebase, the V1.5 build specification, and any relevant documentation regarding user journeys and expected outcomes. Thanks!

@seefattechnologi

YES--------------AI Backend Integration Specialist-------Ready to do this job as its perfect match with my skills I am an CREATIVE/Multitalented AI/ LM/RAG/Evals/TypeScript/Full stack developer having rich experience with all the latest technologies with so many successful Tasks. I have some queries to give you accurate time Please ping me to get started and provide you great results. Thanks!!!

@Rapha

Hi, I'm Rafael. I’ll focus on the backend PHP work needed to make your AI layer dependable: preserve solid AI routing/retrieval pieces, remediate weak tool/action boundaries, and enforce canonical state with idempotent queue/webhook handlers and provider abstraction. One practical idea is to add a small PHP evaluation service that exposes guarded execution endpoints and an acceptance-test harness to replay representative cases against models and providers so regressions are caught early. Do you want PHP to run alongside the existing TypeScript/serverless stack or replace specific backend components? Contact me through Freelancer chat to discuss this project and estimate realistic timing and cost.

@sunainawbst

AI Backend Integration Specialist Hello I have read your project requirements, i can help you develop and integrate your AI Backend effectively. I bring to the table a comprehensive understanding of AI systems, which combines well with my backend engineering expertise. This unique combination helps me create reliable and robust AI products while maintaining the crucial aspects of a traditional backend system such as structured outputs, retrieval, action boundaries, and more. Recently I have been working on Lovable AI for developing a gaming platform using it, complete with chat-based agent logic, expressive front-ends, and backend integrations. See here : In other project, implemented a fully automated AI agent system for intelligent meeting creation using ElevenLabs Conversational AI and Gemini (via a custom agent brain). The flow integrates voice interaction, natural language processing, location precision, and frontend. Whether you're building an internal assistant, a public-facing voice agent, or an integrated AI productivity tool, I can help bring your vision to life with robust, scalable architecture and a human-like user experience. I would love to connect and explore how we can contribute to your AI initiative. Regards Ranjana

@rahuliitm69

Hi, I’ve carefully read the complete brief, and I understand that you’re not looking for a simple chatbot or prompt engineer. You need a senior AI/backend engineer who can audit the existing system and make the LLM/RAG layer reliable, grounded, testable, and tightly connected to the application’s canonical state. I have already developed similar AI-powered platforms involving LLM workflows, RAG/retrieval, structured outputs, TypeScript/Node.js serverless backends, external APIs, background jobs, permissions, state management, observability, and automated AI evaluations. I can work directly with the existing codebase and preserve what is already strong rather than unnecessarily rebuilding it. Two questions: Which LLM/search providers and RAG stack are currently being used? Can you provide access to the existing repository and V1.5 specification for the initial audit? I’m available to start immediately and can provide a fixed quote after reviewing the codebase. Thanks Rahul

@installerpoint

Good Day! I have carefully analyzed your project and can audit and strengthen the existing TypeScript/serverless AI backend with reliable LLM/RAG workflows, structured outputs, canonical state, tool boundaries, evaluations, observability, queues, and production-grade testing. I can work efficiently within the existing architecture, identify gaps, complete the V1.5 requirements, and build a repeatable evaluation system for dependable AI behaviour. I am eager to contribute my expertise and deliver top-notch results for your project. Let's discuss the project further in chat or let's have a quick call! Best regards, M Adeel.

@starttechno

Your V1.5 brief is exactly the right framing: AI can extract, rank and draft, but canonical state, permissions and irreversible actions must remain deterministic backend concerns. I can audit the existing TypeScript/serverless implementation, retain reusable components, and close the gaps needed to make its LLM/RAG workflows grounded, testable and production-ready. I would begin by mapping each AI workflow against the specified state transitions, inputs, outputs and acceptance tests. Then I would harden retrieval with source metadata, permission-aware filtering and citations; enforce schema-validated structured outputs; separate recommendation from tool execution; and make provider calls, queues, webhooks and retries idempotent and observable. I will also add a repeatable evaluation harness using your representative cases and expected outcomes, covering retrieval quality, groundedness, schema compliance, action safety and regression checks. Relevant production work includes fixing a live trading platform where an unthrottled external-data integration froze charts; I introduced caching, provider-credit controls and last-good-value fallback. I have also built an automated QC harness for a generative-video pipeline—useful experience for turning variable AI output into measurable release gates. Muhammad Saad

@athenaesolutions

Hi, Yes, we have experience with production AI/backend systems using TypeScript, Node.js, serverless APIs, structured data, third-party integrations and AI-assisted workflows. We have integrated LLM capabilities into existing products, connecting AI reliably with backend logic rather than building simple chatbot demos. For your project, we will first audit the existing AI/RAG architecture against the V1.5 specification and acceptance criteria. We will review retrieval, structured outputs, state management, provider integrations, permissions and background workflows, preserving what works and fixing the gaps. We will then implement the required improvements with clear AI/backend boundaries, robust error handling and repeatable evaluation tests using your representative cases. This will make the system measurable, grounded and production-ready. We can begin with the audit and provide a clear completion estimate based on its findings. Best Regards, Prabal Dey Codewarrior Technologies

@AneesaIBA

Hello, I have carefully read your project description and understand that you are looking for a skilled professional to audit and complete the AI intelligence and TypeScript/serverless backend layer of your existing product, making the system reliable, grounded, testable, and production-ready. To approach your project I will first audit the existing AI architecture, retrieval pipeline, structured outputs, state transitions, permissions, provider integrations, queues, webhooks, and observability against the V1.5 specification. I’ll preserve strong existing components while improving weak areas and establishing repeatable evaluation cases to measure grounding, consistency, failure handling, and output quality. My focus will be on keeping AI reasoning separate from canonical application state and ensuring every AI action has clear validation and backend control. In terms of relevant experience, I have strong experience building production AI systems using TypeScript, serverless backends, LLM APIs, RAG pipelines, structured outputs, API integrations, webhooks, background workflows, authentication, and evaluation-driven AI development. I’m also comfortable working with inherited codebases and AI coding agents while maintaining proper engineering review, testing, and documentation. I’d love to review the existing architecture and V1.5 specification to identify the highest-risk AI/backend areas first and provide a realistic audit and completion plan. Best Regards, Rabia Shaikh.

@corpmember29

MAKE THE AI LAYER RELIABLE, GROUNDED AND PRODUCTION-READY — NOT JUST ANOTHER CHATBOT DEMO. I have 12+ years of experience in AI, backend and full-stack engineering, including TypeScript, serverless systems, LLM/RAG workflows, structured outputs, APIs, databases and automation. I understand the key requirement: AI should reason and recommend, while canonical state, permissions, external actions and irreversible changes remain controlled by deterministic backend logic. I can handle: • Audit and improve the existing AI/backend architecture • RAG, retrieval, grounding and evidence pipelines • Structured LLM outputs, tool/action boundaries and validation • TypeScript/serverless APIs, queues, webhooks and idempotency • Provider abstraction for models/search services • Evaluation datasets, automated evals and regression testing • Authentication, authorization and canonical state integration • Logging, monitoring, error handling and observability • Performance, reliability and production hardening • Clean documentation and maintainable architecture My approach is Audit → Architecture gaps → AI/backend implementation → Evals → Integration testing → Production hardening. I’m comfortable using Claude/Cursor and other AI coding agents for accelerated development while maintaining human architectural review and strict testing. I can provide a fixed quote after reviewing the existing repository and V1.5 specification. Available to start immediately. Thanks Christina

@doomshellsl

Hi, Making an existing AI product reliable requires more than prompt engineering—it needs strong backend architecture, grounded retrieval, structured outputs, evaluation, and clear control over application state. From your requirements, we understand you need a senior AI/backend engineer to audit, improve, and complete the existing TypeScript/serverless AI integration layer. We’ll audit the inherited AI/backend architecture, identify reliability and integration gaps, improve LLM/RAG workflows, implement structured outputs and evaluation processes, and ensure AI actions remain properly connected to the product’s canonical state. We’ll also address API integrations, authentication, permissions, queues/webhooks, observability, error handling, and production testing. Our approach will focus on making the existing system reliable, measurable, grounded, and production-ready while preserving reusable components and avoiding unnecessary rebuilds. Let’s connect and review the existing architecture and V1.5 specification. We can provide a clear audit plan and complete the required AI/backend work efficiently.

@VirasatSolutions

Hi! I understand you’re not looking for a prompt engineer or chatbot developer. You need a senior AI/backend engineer to take an existing TypeScript/serverless product and make its AI layer reliable, grounded, measurable and production-ready. ++ What I’ll handle: → Audit the inherited AI/backend architecture and identify what to preserve, improve or complete → Strengthen LLM/RAG pipelines, retrieval, grounding and structured outputs → Build repeatable evals, regression tests and acceptance checks → Connect AI workflows to canonical application state with clear tool/action boundaries → Improve APIs, queues, webhooks, idempotency, permissions and state transitions → Add validation, retries, observability and provider abstraction → Complete the V1.5 AI/backend requirements and validate representative cases I bring 10+ years of software engineering experience with strong hands-on expertise in AI/LLM integrations, RAG, Python, TypeScript, APIs, automation and production systems. My approach is simple: first audit the existing implementation against your V1.5 specification, then fix the highest-impact gaps and prove the result through repeatable evaluations and tests—not just a successful demo. I’m comfortable inheriting existing systems, working with coding agents and collaborating around clearly defined acceptance criteria. Available to start promptly and provide the audit/completion quote after reviewing the codebase. - Abhishek

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Reliable AI/Backend Systems with Experience in TypeScript ❇️ Hi My Friend, I hope you're doing well. I have reviewed your project details and see you are looking for an AI/Backend Specialist. You don’t need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in AI and backend systems. I will audit the current implementation, improve weak areas, and ensure the AI is reliable and connected to the product’s core. I will use my experience to enhance the AI layer by building structured outputs and ensuring proper integration with your existing systems. My goal is to deliver a dependable product that meets your specifications within the budget. ➡️ Why Me? I can easily handle your AI/backend project as I have 5 years of experience in AI systems, backend integration, and TypeScript development. My expertise includes structured outputs, retrieval systems, and production testing. Additionally, I have a strong grip on other relevant technologies, ensuring a comprehensive approach to your project. ➡️ Let's have a quick chat to discuss your project in detail. I’d love to show you samples of my previous work. Looking forward to chatting with you!

@Hubready

Hello!, I am a Florida-based senior software engineer who builds AI-backed systems that actually work in production, not just demo-level integrations. Your real need is a senior AI/backend specialist who can connect LLM/RAG workflows, backend logic, and automation into one reliable system without creating a fragile mess. That’s exactly how I work. My approach: 1. Review your current stack, data sources, and workflow gaps 2. Map the AI flow, including retrieval, prompt design, and backend orchestration 3. Build the integrations cleanly in PHP, Java, or JavaScript 4. Test for accuracy, speed, error handling, and maintainability 5. Deliver with documentation so it is easy to extend later I’ve built production systems across AI automation, SaaS platforms, data pipelines, and high-volume backend environments, so I pay attention to the details that usually get missed. Relevant work: - internal AI knowledge assistant for a logistics team - RAG-based support automation tool for a SaaS platform - backend workflow engine for a finance dashboard - API-driven content ops system for an e-commerce brand Quick questions: 1. What is the main AI outcome you want first: search, automation, recommendations, or an internal assistant? 2. Do you already have data sources and APIs ready, or should I help structure that layer too? 3.