Temporal-Driven AI Recruitment Platform

@neerajdhameliya

Hello, I’d design the PostgreSQL schema with dedicated JSONB evaluation traces and use Temporal to manage workflow state. This lets the Shortlisting agent apply fast, deterministic filters before calling Hermes 3, reducing LLM costs and candidate-processing time. I can handle the full implementation, from Temporal workflows for multi-channel publishing and outreach to a clean, fully typed REST API. With 9+ years building event-driven systems and stateful microservices, I deliver production-ready code with E2E workflow tests, documentation, and performance benchmarks. Would you be open to sharing the PRD before a call? I’d like to review your latency targets and shortlisting criteria. Best, Niral

@corpmember29

Hello, I read your requirements carefully and understand that you need a production-ready AI recruitment platform built around Temporal workflows, PostgreSQL and Nous Hermes 3 agents. I have 10+ years of experience in the required technologies and can take ownership of the full-stack implementation from architecture through deployment. >>> 40-45 hours weekly I am available for work<<<< >>> you will track all progress of the project thru the tracker <<< I will build the Temporal workflow layer for publication, marketing, candidate shortlisting, ATS and analytics processes, design a scalable PostgreSQL data model, integrate Hermes 3 reasoning agents, and expose clean APIs for communication between services. The architecture will support asynchronous workflows, retries, failure handling, workflow state persistence and observability. The platform will include the ATS foundation, candidate/application management, automated recruitment workflows, agent orchestration, analytics and reporting, role-based access and API integrations. I will also implement automated testing, workflow validation, performance monitoring and clear technical documentation so the platform can evolve without architectural rework. I WILL PROVIDE 2 YEAR FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE, WE WILL WORK WITH AGILE METHODOLOGY AND WILL GIVE YOU ASSISTANCE FROM ZERO TO PUBLISHING ON STORES. Thanks, Christina

@nitinsaluja98

Hi, I can build am reliable Temporal workflows, integrate Hermes 3 agents for intelligent decision-making, and keep the ATS modular and scalable for future growth. My approach would be to first design a clean PostgreSQL schema and Temporal workflows, then integrate the Hermes 3 agents for publication, marketing, and candidate shortlisting before exposing secure, well-documented APIs for other microservices. I focus on writing clean, maintainable code, adding end-to-end tests, optimizing performance, and documenting everything for long-term scalability. I have built AI platforms involving LLMs, RAG pipelines, workflow automation, analytics dashboards, and microservice-based systems, and I'm looking for a long-term collaboration where I can take ownership of the platform. Before we get started, I have a few questions: *Will Hermes 3 agents run locally or through an external API? *Is the PRD detailed enough to define the Temporal workflows, or would you like me to help design them as part of the implementation? I'd be happy to review the PRD, discuss the architecture, and start immediately. Kind Regards, Nitin

@mubeenm5026

As the founder of Web Crest, a seasoned software development firm, I leverage my extensive experience in API development and full-stack development to craft intelligent, scalable solutions that meet and exceed client expectations. A confident Python coder, I have orchestrated countless workflows utilizing Temporal and honed my skills working with Postgresql for database management; a crucial component in your specifications. Not only will I wire Temporal to a solid Postgresql schema, but also ensure efficiency with clear documentation and reproducible analytics dashboards. One of our expertise at Web Crest lies within AI-powered applications and automation workflows, aligning seamlessly with the Temporal-driven nature of this project. With knowledge in AI agents and job-specific content distribution, I'll build the publication and marketing agents that push openings to multiple channels while driving targeted outreach respectively. Additionally, from reviewing your Project Requirement Document (PRD), I fully understand the importance you place on clean code and on-time deliveries. My development approach is based on Agile Project Management principles ensuring

@tangramua

Dear ,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in Python, PostgreSQL, Full Stack Development, API Development, AI Agents, Hermes Agent and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@ShaikhAneesa

Hi there, I understand you’re moving from a completed PRD into production for an AI recruitment platform built around Temporal, PostgreSQL and Nous Hermes 3, with Publication, Marketing and Shortlisting agents feeding into the ATS and analytics layer. I’m confident I can build the architecture so the agents, workflows and API layer remain modular, testable and scalable as the platform grows. My approach is to first translate the PRD into a clean PostgreSQL data model and Temporal workflow architecture, then implement the core APIs and Hermes 3 agent services with clear boundaries between reasoning, deterministic business logic and workflow orchestration. I’ll build the Publication, Marketing and Shortlisting workflows with retries, state management and failure handling, then connect ATS, analytics and reporting around the same underlying data. Each sprint will include end-to-end workflow tests, reproducible reporting and latency testing under realistic load. You’ll receive production-ready source code, Temporal workflows, PostgreSQL schema, Hermes 3 agent integration, API layer, automated tests, analytics/reporting components and clear technical documentation for continued development. Would you like to review the PRD first and define the first end-to-end recruitment workflow as the initial sprint? I’m ready to start immediately. Warm Regards, Aneesa

@denisSolution

Hi, This looks like a solid agent orchestration problem where the main challenge is keeping the workflows reliable under real load while keeping the Hermes agents focused and the PostgreSQL layer clean. I’ve built similar agent-driven backbones before, most recently on a hiring-adjacent internal tool that tied multiple AI agents into a single workflow engine. I’d start with a stable Postgres schema that maps cleanly to the Hermes agent outputs, then wire Temporal to handle the orchestration with clear failure states and retries. The API layer would sit on top of this, exposing just enough surface for other services to trigger workflows without leaking internal complexity. The analytics part is usually the trickiest—if we start with a minimal dashboard that aggregates the agent logs into a few high-signal views, we can expand later once usage patterns settle. One potential risk is Hermes’s reasoning latency under heavy filtering loads; we might need to cache common query patterns or push some of the heavy lifting into background jobs. Also, the Publication agent’s channel integrations could surface inconsistent rate limits, so building a small rate-limiter into the Temporal workflows would help. If this setup aligns with what you’re aiming for, let’s walk through the PRD together and lock in the first sprint. Thanks, Denis

@DeveloperStation

Hi, I built a secure CI pipeline with deterministic ingestion where the tricky part was keeping AI-driven steps reproducible under test, work close to your end-to-end orchestration and latency goals. Secure CI Pipeline & Deterministic Ingestion: 5★ contract, ai automation work One question on Temporal: do you want each agent (Publication, Marketing, Shortlisting) as its own workflow with activities, or one parent workflow fanning out to child workflows? That choice drives the Postgres schema and retry model, so I'd settle it before wiring the first sprint. On the AI side, we've built agent-driven tools on OpenAI and Claude APIs, including an AI resume generator and an AI business-development automation system on Laravel and Redis. Send the PRD and I'll map the first Temporal workflow against your schema. Adil

@maxscender

I can help you own the build-out of the Temporal-driven AI recruitment platform. I’ll start by wiring Temporal workflows to a Postgres schema that supports the full pipeline, then stand up Hermes 3 agents for publication, marketing, shortlisting, and analytics. The API layer will be clean, typed, and built for other microservices to consume. I’ll prioritize passing end-to-end tests, reproducible dashboards, and latency under load from day one. My focus is clean, scalable code and clear docs, so the platform stays maintainable as we grow it together.

@Rekhathakur

Hi, I’d be very interested in building your AI-powered recruitment platform. The combination of Temporal, PostgreSQL, AI agents, and a scalable API architecture is a strong fit for my full-stack and AI development experience. I would approach the build in clear milestones: Design the PostgreSQL schema and core domain architecture. Set up Temporal workflows and activities with reliable retries and error handling. Integrate Hermes 3 agents for reasoning-based recruitment workflows. Build a clean API layer for communication between services. Develop the Publication, Marketing, Shortlisting, ATS, and Analytics components. Implement end-to-end workflow testing and latency monitoring. Build reproducible analytics and reporting. Document the architecture, APIs, workflows, and deployment process. I would keep the AI agents focused on reasoning while using deterministic business logic for critical recruitment rules, making the platform more reliable and easier to maintain. I’m comfortable working from a detailed PRD, taking ownership of the technical implementation, and collaborating long-term as the platform evolves. I’m available to start immediately and would be happy to review the PRD with you and define the first sprint and acceptance criteria. Best regards,

@toriquldev123

Hello There! I’m Md Toriqul Islam, an experienced full-stack developer with 10+ years of experience, and I’m excited to partner with you. I understand you need an AI-powered recruitment platform using Temporal for workflow orchestration, PostgreSQL for data, Hermes 3 agents for reasoning, and APIs connecting publication, marketing, shortlisting, analytics, and ATS workflows. I am skilled in Node.js, Python, PostgreSQL, REST APIs, AI integrations, microservices, Docker, and workflow automation. I’m ready to start immediately and would be happy to review the PRD and discuss the architecture. Looking forward to hearing from you. Best regards, Md Toriqul Islam

@mayankinnovative

The core challenge is coordinating multiple AI agents into a reliable recruitment pipeline—not simply connecting an LLM to an API. Publication, outreach, shortlisting, analytics and ATS workflows need to execute predictably, retain state, and remain observable as candidate volume grows. I’d start by mapping the PRD into Temporal workflows and activities, defining a PostgreSQL schema around candidates, jobs, applications and workflow state. Hermes 3 agents would then be isolated behind clear interfaces so their reasoning can be tested and replaced without rewriting orchestration logic. I’d expose the platform through a well-defined API layer for downstream microservices, with the ATS acting as the central source of application state. Analytics would consume structured events rather than agent output directly, making reporting reproducible and easier to validate. For each sprint, I’d test complete workflow paths—including retries and failure scenarios—then benchmark candidate-facing API/agent latency under representative load. Documentation would cover architecture, workflows, APIs and local deployment so the system remains understandable as the team expands. My relevant background is building AI-agent workflows and backend systems, particularly around coordinating automated reasoning with application logic. Would you like to start by reviewing the PRD and identifying the first Temporal workflow to implement?

@ishtiaqn2o

Hello, Hope you are doing well. I’d be interested in working on this. I have experience with Python, PostgreSQL, REST APIs and AI/LLM integrations, and I’m comfortable building scalable backend systems around workflow orchestration. I’d start with the PostgreSQL schema, Temporal workflows and Hermes 3 agent integration, then build the API layer for the other services. I’d keep the architecture modular so the Publication, Marketing, Shortlisting, ATS and Analytics components can evolve independently. I’ll also focus on reliable workflow retries, error handling, testing and performance from the beginning. Please share the PRD and I can review it and suggest the best approach. Kind Regards

@abdulhamidh2

Hello I just read about your project building an AI-powered recruitment platform using Temporal, Postgresql, and Hermes 3 agents, and it sounds like an exciting challenge. I specialize in full-stack development with strong expertise in Python, PostgreSQL, and API design, which perfectly aligns with your tech stack. Here’s how I’d handle it: I’ll start by designing a robust Postgresql schema optimized for Temporal orchestration, then implement Hermes 3 agents to manage reasoning workflows efficiently. I focus on clean, scalable code with thorough documentation to ensure maintainability and smooth collaboration. My experience includes building real-time data pipelines and integrating AI agents into production systems with solid testing practices to meet performance benchmarks. Could you share the PRD so we can review it together and plan the first sprint? Best regards, AbdulHamid

@juanpablomacf

Jumping right in — getting Temporal wired cleanly to Postgres and exposing a stable API layer is exactly the kind of backend foundation I’m used to building. I’ve worked on multi‑agent systems where orchestration, reasoning endpoints and ATS‑style pipelines all need predictable latency, plus clear docs so the stack can grow. I’d start by shaping the DB schema around your PRD, then binding Temporal workflows to Hermes 3 agents and exposing the service layer for other components. Quick checks: will agents share a common memory store or isolated contexts? is your ATS data model already final? should analytics live inside the core service or a separate microservice? Juan Pablo

@HamparProd

Hi, The important part of this platform is separating deterministic recruitment workflows from probabilistic agent reasoning. I would use Temporal as the durable orchestration layer and keep Hermes 3 agents focused on bounded tasks such as candidate evaluation, outreach generation and reasoning, rather than allowing agents to own workflow state. I’d start by translating the PRD into Temporal workflows/activities and a PostgreSQL domain model covering jobs, candidates, applications, workflow state, agent outputs, audit history and analytics events. From there I can implement the Python API/service layer, Hermes 3 inference integration, structured agent outputs, retries/timeouts, idempotent activities and observability. Agent decisions can retain model/version, inputs, outputs and relevant reasoning metadata so recruitment actions remain traceable rather than becoming opaque LLM calls. For shortlisting, I’d also separate hard eligibility rules from AI-assisted scoring. That makes results easier to test, explain and tune while keeping sensitive hiring decisions under explicit application control. I’m comfortable owning this from architecture through implementation, automated testing, Dockerized deployment and documentation, and continuing through subsequent product iterations.

@vishal1145

Your Hermes 3 agents will fail under concurrent load if you don't implement proper rate-limiting and queue management between Temporal workflows and the LLM inference layer. Without this, your Shortlisting agent will bottleneck when 200+ applications hit simultaneously during a job posting spike. Quick questions - what's your target latency for the Shortlisting agent when processing 500 applications in parallel? And are you planning to self-host Hermes 3 or use an API endpoint with token limits? Here is the architectural approach: - TEMPORAL WORKFLOWS: Design durable execution patterns with compensation logic so failed agent calls don't corrupt your candidate pipeline or leave orphaned records in PostgreSQL. - HERMES 3 AGENT ORCHESTRATION: Build a prompt-caching layer and implement circuit breakers to prevent cascading failures when the reasoning model hits rate limits or times out. - POSTGRESQL SCHEMA: Structure normalized tables with JSONB columns for agent metadata, indexed on candidate_id and workflow_run_id to support sub-100ms analytics queries at scale. I've built similar agent-orchestration systems for 2 HR-tech platforms that process 10K+ candidates monthly without degradation. Let's schedule a 20-minute architecture review to align on your Temporal workflow design before you commit to a build.

@Aaleen110

The core of this is Temporal orchestrating Nous Hermes 3 agents and Postgresql data, so I'll structure the build around that. We'll start by defining the Postgresql schema for applicant data, job postings, and channel integrations, then wire Temporal workflows to manage the agent interactions. The Publication agent will push jobs, the Marketing agent will handle outreach, and the Shortlisting agent will filter applicants in real-time, all driven by Hermes 3 reasoning. The API layer will expose these functions for other microservices. I'll assume the API will be RESTful over HTTP for broad compatibility. The brief doesn't specify how the analytics and reporting will be surfaced, so I'll plan for a separate reporting API endpoint until you advise otherwise. Preferred Freelancer here, and I have not missed a deadline or gone over an agreed price yet. What is the existing infrastructure for the multiple channels the Publication agent will push to? Send over the requirements doc to begin.

@melikatfz

Hi there, Navigating the complex integration of AI agents like Hermes 3 with Temporal and ensuring seamless API communication can be challenging. If not executed well, it risks data mismanagement and inefficient workflows. With my expertise, I offer a robust, scalable solution, ensuring your recruitment platform runs smoothly and grows efficiently. Before we proceed, here are my questions: What is the expected timeline for the initial milestones? Can you specify any preferred frameworks or libraries for the API layer? Let's discuss your project now!