AI Engineer to build AI Receptionist for Lender

We are looking for a hands-on Voice AI Engineer to own the technical delivery of an enterprise voice automation program for an industrial equipment and services business.

You will take the solution from discovery and architecture through agent development, integrations, testing, deployment and ongoing optimisation. The initial focus is inbound calls across service, parts and rental, with approximately 300 calls per day.

This role suits someone who can turn a working demonstration into a reliable production service and work directly with customer teams to make it effective.

What you will build

A connected Voice AI solution that answers calls on existing business numbers, identifies customers and equipment, understands requests and routes conversations to the appropriate workflow.

The solution will capture structured call records, integrate with existing CRM and service-management systems, and transfer urgent or complex calls to people. Customer and equipment information will come from a database refreshed through scheduled data synchronisation.

Your responsibilities

• Own technical delivery: Translate business requirements into architecture, implementation plans, integration specifications and acceptance criteria.
• Build voice agents: Develop reception and specialist agents for service, parts and rental, with shared context and reliable hand-offs.
• Improve conversation quality: Configure speech recognition, voice generation and language models. Optimise latency, interruptions, turn-taking, pronunciation and handling of background noise.
• Implement telephony: Configure inbound routing, existing-number connectivity, concurrent calls, live transfers, after-hours handling and fallback routes.
• Connect business systems: Build APIs, webhooks and middleware for CRM, service queues and customer databases. Implement scheduled synchronisation, retries and duplicate prevention.
• Capture usable records: Generate accurate summaries and structured fields covering customer details, equipment, reason for calling, urgency, outcomes and relevant sales interest.
• Build safeguards: Implement call-duration and monthly-usage caps, alerts, escalation rules and checks that requests have been successfully logged.
• Test and launch: Develop realistic test scenarios, run integration and load testing, support customer acceptance testing and manage production deployment.
• Operate and improve: Monitor call quality, integration failures, latency and cost per minute. Investigate incidents and refine agent behaviour using transcripts and customer feedback.
• Document the solution: Maintain architecture diagrams, configuration records, deployment procedures and operational runbooks.

What we are looking for

• Strong development skills in Python and/or JavaScript/TypeScript.
• Experience shipping at least one Voice AI or conversational AI solution into production.
• Hands-on understanding of speech-to-text, text-to-speech, language models and tool/function calling.
• Experience with telephony APIs, SIP, call routing and human transfers.
• Strong API integration skills, including authentication, webhooks and asynchronous processing.
• Working knowledge of SQL databases, data synchronisation and cloud deployment.
• Experience with logging, monitoring, error handling and production troubleshooting.
• Ability to implement secure access, protect personal information and manage recordings and transcripts appropriately.
• Confidence working directly with customers, explaining technical trade-offs and taking ownership of delivery.

Useful additional experience

• Multi-agent orchestration and context management.
• Integration with enterprise CRM, workflow or document-management platforms.
• Retrieval-based knowledge systems and structured information extraction.
• Contact-centre, field-service, equipment rental or industrial service workflows.
• Automated conversation testing and evaluation.

What success looks like

• A stable deployment that meets agreed call-handling and integration targets.
• Clear, natural conversations with appropriate escalation to people.
• Accurate service requests and sales leads reaching the correct systems.
• Reliable controls over usage, cost and failure handling.
• Measurable improvements following testing and customer feedback.

Why join

You will own a live enterprise implementation from the first technical discussion through production operations. You will have direct access to decision-makers and the opportunity to build reusable components for future Voice AI deployments.

How to apply

Share your CV and a brief description of a Voice AI solution you have built. Explain your personal contribution, the integrations involved and one production challenge you solved.

The Role

We’re looking for a Senior Applied AI & Data Engineer to become our first dedicated AI and data engineer.

You’ll build conversational AI experiences across web, mobile, and in-store channels while developing the data foundation behind them. You’ll make key technical decisions and own your work through to production.

What You’ll Do

• Build AI assistants using tool calling to work with real product, search, and order systems

• Design guardrails and evaluation sets to ensure AI responses are accurate and safe

• Build real-time and voice-enabled AI experiences

• Improve product data quality through AI-assisted enrichment and review workflows

• Build data pipelines, analytics, and personalisation systems

• Work closely with web and mobile developers and help guide technical implementation

What You’ll Need

• 6+ years of experience building and running production backend systems

• Strong Python skills, plus experience with JavaScript/TypeScript backends

• Experience shipping at least one LLM-powered feature to real users

• Experience with search and relevance

• Experience building data pipelines and analytics stores

• Comfortable deploying and monitoring services on a major cloud platform

• Strong communication skills and the ability to work independently

Nice to Have

• Experience with speech or voice AI

• E-commerce or retail technology experience

• Experience building multilingual products

AI / Backend Engineer — Remote (India / Overseas)

Company: Ink'd

Compensation: $1,500–$2,500 USD/month, depending on experience

Type: Independent contractor, long-term opportunity

Ink'd is building a voice-first AI platform for residential real estate transactions. Our AI assistant allows real estate agents to generate contracts, automate workflows, and complete transaction documentation through natural conversation.

We're looking for a highly capable AI/backend engineer to help scale and maintain our production platform.

Responsibilities

• Build and maintain production AI agent workflows
• Develop integrations with third-party APIs and services
• Work with LLMs, structured data extraction, and document generation
• Troubleshoot production systems and improve reliability
• Build scalable backend services and maintain databases
• Collaborate directly with the founder and engineering team

Technical experience

• Python, FastAPI, Node.js, and REST APIs
• LLM APIs, tool calling, and agent orchestration
• PostgreSQL and cloud infrastructure
• GitHub, CI/CD, debugging, and deployment
• Experience with voice AI, WebSockets, or document processing is a major plus

What we're looking for

Someone who has independently shipped production software, can troubleshoot unfamiliar systems, communicates clearly, and takes ownership of their work.

Please include your GitHub, two examples of production systems you've built, your specific contributions, monthly compensation expectations, and availability.

Job Description-

Location- Bengaluru

Experience-5-7 years

Wissen is building the engineering team for RES Modernization, a corporate services programme at a leading global financial services firm, rebuilding the lease and real estate management platform on a cloud stack with AI and agentic capability designed in rather than bolted on. The AI Solution Engineer builds that product: .NET services and APIs at the core, Python wherever the AI, retrieval and data work lives. We want a strong .NET engineer who has moved into Python, not a Python specialist who once touched C#.

• Build features end to end on a .NET codebase: C# and ASP.NET Core services, the APIs above them, and the React or Angular front end where a feature needs one.
• Write the Python that carries the AI work — retrieval and grounding, prompt and agent orchestration, evaluation harnesses, and the pipelines that feed them.
• Put LLM and agentic capability into real product workflows, with the grounding, guardrails and cost and latency budgets a regulated environment demands.
• Take your work through the client's engineering and change review: design notes, test evidence, security and code-quality gates.
• Work with the stream's data and integration engineers on the Snowflake and integration layer the product reads from.

About LeadSquared

LeadSquared is a leading sales execution and marketing automation platform trusted by 2,000+ businesses globally, including healthcare, education, financial services, and real estate. Headquartered in Bengaluru with offices across the US, UK, UAE, and Southeast Asia, we empower sales teams to close faster, smarter, and at scale.

Our AI team is at the forefront of integrating cutting-edge large language model capabilities into enterprise workflows — building intelligent agents, copilots, and automation systems that redefine how businesses operate.

Role Overview

We are looking for a Senior AI Engineer with hands-on experience building LLM-powered agents and agentic AI systems. You will design, develop, and deploy autonomous AI pipelines that solve complex, multi-step business problems — from lead qualification and follow-up automation to intelligent CRM workflows and beyond.

This role is ideal for someone who is deeply excited about the frontier of AI, can move fast, and wants their work to directly impact millions of sales professionals worldwide.

Key Responsibilities

•

Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.

•

Develop and maintain Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate, Chroma, pgvector) for domain-specific knowledge grounding.

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Build and integrate tool-use and function-calling capabilities into AI agents, enabling dynamic interaction with internal APIs, databases, and third-party services.

•

Implement prompt engineering strategies including chain-of-thought, few-shot prompting, and structured output parsing to ensure reliable agent behavior.

•

Design evaluation frameworks and observability pipelines (LangSmith, Helicone, custom metrics) to monitor agent performance, accuracy, and cost.

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Collaborate with product, sales, and domain teams to translate business requirements into AI-driven solutions and features.

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Optimize LLM inference for latency and cost using techniques like caching, model distillation, quantization, and batching.

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Stay current with the rapidly evolving LLM ecosystem and proactively propose improvements and new approaches.

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Contribute to internal best practices, documentation, and knowledge-sharing across the engineering org.

Required Qualifications

Experience

•

2–4 years of professional software engineering experience, with at least 1–2 years focused on LLM/AI systems.

•

Proven experience shipping LLM-based products or agentic AI systems into production environments.

Technical Skills

•

Strong proficiency in Python and familiarity with async programming patterns for AI pipelines.

•

Hands-on experience with LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), or open-source models (Llama, Mistral).

•

Experience with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.

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Solid understanding of RAG architectures, embedding models, and semantic search.

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Experience with vector databases and similarity search infrastructure.

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Knowledge of REST APIs, microservices architecture, and containerization (Docker/Kubernetes).

Problem-Solving & Mindset

•

Strong ability to decompose ambiguous, open-ended problems into structured AI system designs.

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Experience with prompt debugging, LLM evaluation, and iterative refinement workflows.

•

Ability to balance research exploration with engineering pragmatism to ship reliable systems.

Preferred Qualifications

•

Experience with multi-agent orchestration and agent memory systems (short-term and long-term).

•

Familiarity with fine-tuning or RLHF workflows for domain adaptation.

•

Background in NLP, information retrieval, or conversational AI.

•

Prior experience in B2B SaaS or CRM domain is a plus.

•

Contributions to open-source AI/ML projects or published research/blogs.

•

Experience with cloud platforms: AWS, GCP, or Azure — particularly AI/ML services

About the Company

The client is revolutionising the way businesses operate through cutting-edge technological solutions. Their focus is on developing intelligent agents and agentic workflows that automate processes and eliminate the need for human effort wherever possible. By leveraging

advanced AI and machine learning, they create systems that enhance productivity and drive efficiency.

Their expertise extends to the fintech, healthcare and medical technology sectors, where they develop innovative solutions that improve patient outcomes and streamline medical operations.

From medical devices to healthcare platforms, their work sits at the intersection of technology and medicine, pushing the boundaries of what's possible. The team is dedicated to continuous learning and growth, ensuring the team members are always at the forefront of the tech landscape.

About the Role

This is a senior, hands-on engineering role at the heart of our product team. You will be one of the most technical people in the room — setting the architecture for our real-time voice AI

agents and building the hardest parts of it yourself. From the systems that power live conversations to the interfaces our clients rely on, you will own how the product is engineered end to end.

We are looking for a genuine lead full-stack engineer with the depth to make architecture decisions that hold up as we scale, and the appetite to still be in the code every day. You should be as comfortable designing the backend services behind a live voice agent as you are shaping a clean interface on top of them — and comfortable being the person others turn to when something is hard.

You will work directly with the founder and product leadership on a fast-moving product, with real influence over technical direction. This is a role for someone who wants ownership at the level of "how the whole thing is built," not just individual features — and who raises the bar for

everyone around them.

What You'll Own

Set the technical direction

• Own the architecture of our core systems — the real-time voice agents, backend
• services, data and APIs — making the decisions that keep the product fast, reliable and scalable as it grows.
• Lead the hardest engineering problems and solve them personally.
• Establish engineering standards — code quality, review practices, testing and technical patterns that the team builds to.
• Drive technical strategy with the founder and product leadership — shaping the roadmap, flagging risk early, and turning product ambition into a sound technical plan.

Build the product end to end

• Design, build and ship features across the stack — backend services, APIs and front-ends — owning them from idea to production.
• Build the client-facing surfaces — dashboards, review tools and configuration interfaces that let our clients run and trust the product.
• Design and evolve the data models and APIs that hold up as we scale across clients.

Make it reliable and fast

• Own production quality — put the monitoring and alerting in place so issues are caught before clients feel them, and performance stays within target.
• Care about performance — find and fix bottlenecks across the stack.
• Build for correctness — put the testing and evaluation in place that keeps the product behaving predictably as it changes.

Lead through the team

• Mentor and grow engineers — through code review, pairing, and setting a technical example others learn from.
• Multiply the team's output — unblock others and lift the overall quality of the codebase.
• Take features from ambiguity to done — turn a rough product goal into a shipped, working capability with minimal hand-holding, and help others do the same.

What We're Looking For

• 8+ years of professional software engineering experience, with significant depth across backend and a track record of owning systems, not just features.
• Strong backend engineering, ideally in Python — building and scaling production services and APIs..
• Proven architecture and system-design ability — you have designed systems that scaled, and can reason clearly about trade-offs.
• Solid fundamentals across APIs, databases and cloud infrastructure.
• Experience building real-time and/or AI-powered products — or clear, demonstrable ability to lead in this area.
• A history of technical leadership — setting standards, mentoring engineers, and being trusted with the hardest problems — while remaining hands-on.
• Excellent communication and a genuine ownership mindset — someone who can be handed an ambiguous, high-stakes problem and be trusted to see it through.

Nice to Have

• Experience working with AI / large language models in production.
• Experience with voice or other real-time products.
• Exposure to healthcare, fintech, or other regulated / high-stakes domains.
• Experience as an early or senior engineer in a startup, where you set direction and wore many hats.

About the Role

We are a 25-year-old company building toward a technology-centered workforce where AI agents and automation handle more of the day-to-day work, supported by people with specialized expertise.

We are automating our existing workflows, expanding our use of agentic AI, launching a sister company next year, and building a fleet of Hermes AI agents to delegate and manage work.

We are looking for a hands-on AI Systems Architect & Company Technology Lead to help build, connect, and continuously improve these systems.

Key Responsibilities

·       Own and improve our Microsoft 365 technology environment and AI-powered workflows.

·       Build automations connecting email, meetings, Planner, and other business systems.

·       Research, test, implement, and maintain AI tools and integrations.

·       Build and manage the Hermes agent fleet, including shared memory, delegation rules, workflows, and reporting.

·       Connect AI agents to business systems and SaaS platforms using APIs, webhooks, databases, and automation tools.

·       Help build an internal agentic marketing department by selecting and connecting the right AI tools.

·       Continuously troubleshoot, improve, and document our technology systems.

·       Help apply these systems as the company expands into new ventures.

Must-Haves

·       Strong technical problem-solving and self-teaching ability.

·       Solid hands-on experience building, configuring, and managing AI agents.

·       Experience connecting AI agents and multiple SaaS platforms using APIs, webhooks, databases, and automation tools.

·       Comfortable with Python, JavaScript, or similar.

·       Ability to independently research, build, test, troubleshoot, and improve systems.

·       Strong interest in AI, automation, and emerging technology.

This is a rapidly changing field therefore Direct experience working with actual Hermes agents is not required. However, hands-on experience working with AI agents is required.

What we need is someone who already understands the fundamentals of deploying AI agents, giving them instructions and tools, connecting them to other systems, and making them work reliably in a real business environment.

The Opportunity

This is an opportunity to help us discover and implement what is actually possible with AI today, and to lead the process of expanding workflows along with the rapidly advancing capabilities — this role is not only to implement a technology that has already been figured out.

Role Overview 

We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale. 

Key Responsibilities 

Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production. 

Write clean, tested, production-grade code and participate actively in code and design reviews. 

Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production. 

Required Qualifications 

8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs. 

Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel). 

Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers. 

Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability. 

About the company

We are an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models.

Our Past

We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Team

Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role focuses on healthcare and RCM, working alongside our AI/ML engineers, data scientists and domain specialists.

Work you’ll do

We are looking for an experienced AI engineer with hands-on experience in healthcare and revenue cycle management (RCM). You will build and deploy AI agents, automations and data workflows for healthcare operations, with a focus on the US market.

The work includes payer-portal automation for claim status and EOB retrieval, voice agents for payer follow-up, analysis of claim journeys and bottlenecks, and AI-assisted insights into practice performance. You will work directly with billing and operations teams, owning delivery from understanding the workflow through deployment, evaluation and ongoing improvement.

Responsibilities

• Own AI agent and automation workflows from requirements through design, development, deployment and monitoring.
• Build agents that work across payer portals, healthcare documents, practice-management systems, EHR-connected tools and voice channels.
• Turn fragmented healthcare data into validated, structured inputs for automation and analysis.
• Work directly with billing and operations teams to understand workflows, resolve exceptions and improve systems based on user feedback.
• Evaluate workflow accuracy and completion rates using representative test sets. Monitor failures and operating costs, and implement retries, exception queues and human escalation
• Implement approved privacy and security controls for sensitive healthcare data, including access restrictions, audit trails and safeguards against exposing patient information in logs or model inputs.
• Diagnose and improve failures across data ingestion, integrations, agent execution and user-facing workflows.
• Measure operational outcomes, such as time saved, reduced manual effort and faster turnaround, with the teams using the systems.

Who you are

You are a passionate and results-oriented engineer who is driven by the potential of AI/ML to revolutionize processes, enhance products, and ultimately improve user experiences. You thrive in dynamic environments and are comfortable navigating ambiguity. You possess a strong sense of ownership and are eager to take initiative, advocating for your technical decisions while remaining open to feedback and collaboration.

You are adept at working with real-world, often imperfect data, and have a proven ability to develop, refine, and deploy AI/ML models into production in a cost-effective and scalable manner. You are excited by the prospect of making US healthcare operations faster and more reliable, for the people who run them and the patients they serve.

Skills & Requirements

Must have

• At least 2 years of professional AI engineering experience, including deploying and supporting systems used in real operations. Internships and academic projects alone do not meet this requirement.
• Hands-on experience building AI or automation solutions for healthcare RCM workflows, such as claim status checks, accounts receivable follow-up, denial management, payment posting or payer interactions.
• Practical understanding of how billing teams work, how claims move through the revenue cycle, and how incomplete data and exceptions affect execution.
• Experience deploying and supporting an LLM-based application or AI agent in production, using capabilities such as retrieval-augmented generation (RAG), tool calling or multi-step workflows. Ability to explain your engineering contribution, how the system was evaluated, what failed and how you addressed it.
• Strong production Python and SQL skills, experience integrating APIs, and working knowledge of JavaScript/TypeScript for browser automation or application integration.
• Experience automating workflows across APIs, browsers or user interfaces, using tools such as Playwright, Selenium or UiPath, with error handling and human escalation where needed.
• Experience deploying and monitoring applications on at least one cloud platform—AWS, Azure or GCP—using containers, version control and automated testing.
• Experience handling imperfect inputs such as scanned PDFs, inconsistent portal layouts or incomplete records, with validation and exception handling.
• Experience working directly with billing or operations teams, improving systems based on their feedback, and demonstrating outcomes such as time saved, claims processed or reduced turnaround time.
• Experience handling sensitive healthcare data through appropriate access controls, secure logging and approved data-handling practices.

Preferred experience

• Experience delivering solutions for US healthcare providers, RCM companies or payer-facing operations, including working with US billing teams and payer workflows.
• Experience with practice-management or EHR integrations, payer portals, explanation of benefits (EOB) documents or electronic remittance advice (ERA) data.
• Experience analyzing claim histories, revenue-cycle bottlenecks or practice performance.
• Eperience building voice agents or integrating speech-to-text and text-to-speech services is a plus.
• Familiarity with Model Context Protocol (MCP) integrations.
• Experience with Kubernetes, serverless applications or event-driven architectures.

Working with us

We are a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundaryless.

Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:

✅ Real-time self-coding based on tasks  

✅ Autonomous multi-agent collaboration  

✅ AI-powered decision-making  

✅ Cross-platform compatibility (Desktop, Web, Mobile)  

We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.

### Responsibilities:

- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)  

- Integrate large language models (GPT-4o, Claude, open-source LLMs)  

- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)  

- Work on real-time task execution pipelines  

- Build cross-platform apps using Electron or Flutter  

- Implement Redis, Vector databases, scalable APIs  

- Guide the architecture of autonomous, self-coding AI systems  

### Must-Have Skills:

- Python (advanced, AI applications)  

- AI/ML experience, including multi-agent orchestration  

- LLM integration knowledge  

- Full-stack development: React or Next.js  

- Redis, Vector Databases (e.g., Pinecone, FAISS)  

- Real-time applications (websockets, event-driven)  

- Cloud deployment (AWS, GCP)  

### Good to Have:

- Experience with code-generation AI models (Codex, GPT-4o coding abilities)  

- Microservices and secure system design  

- Knowledge of AI for workflow automation and productivity tools  

Join us to work on cutting-edge AI technology that builds the future of autonomous software.