Conversation Designer / Prompt Engineer (AI Agent Experience)

AI Product Builder | Consumer Experiences

TL;DR: ₹1 lakh/month. HSR Layout, Bengaluru. Full-time, in-person preferred, with flexibility for an exceptional fit. Use AI to build and refine consumer experiences. No CV or prior experience required. Apply by email, then an unpaid 48-hour workout assignment.

I'm Vishnu, building Aira. AI is the biggest equaliser we have, but nobody has figured out the consumer use case yet. I think Aira will be the reason everyday people start using AI daily.

I don't believe chatting is the final interface for AI. So Aira is built around a hand-drawn character that feels alive, shapes what's on your screen, and brings voice, animation and music together. The goal is the best answer, delivered in the best way for your situation, with help acting on it.

Say you're deciding what to cook. Aira helps you pick a meal, shows the ingredients, arranges the purchase with your confirmation. While you cook, it keeps the recipe and your current step on screen, speaks short instructions, and waits while your hands are busy. The same screen won't work at the gym, in meditation or while fixing a tyre. The conversation, the actions and what you see and hear should feel like one experience that adapts to what you're doing.

I'm hiring people who would have wanted to work on the first iPhone. People who obsessed over the small details that made something unfamiliar feel natural, and cared about what a person felt the first time they used it.

We've built the foundation. Your job is to take an experience, decide how it should work, build it with AI, and keep agonising until it feels right. In practice: tuning prompts and behaviour files, building or changing screen components with AI, and testing what you've made.

You may not yet be able to explain why an interaction feels incomplete. I want you to follow that feeling and build a better version. That's why we don't ask for a CV, prior experience or a coding background. We need product thinking, creativity and ownership — you question what AI gives you, make it work, and keep improving it.

We're launching in San Francisco this month. You'll work directly with me and help shape what people experience the first time they meet Aira.

The process

You'll build a workout experience from a minimal starter. We give you a stepper, a timer and the component plumbing; you decide how it behaves and build the rest. Anyone can attempt it, before any screening. You have 48 hours after receiving it. It's unpaid, for evaluation only, and your work stays yours.

AI helps me review, but I pick the shortlist myself. Shortlisted candidates get a 30-minute conversation. I aim to reply within 24 hours of submission and finish within a week.

About MyOperator

MyOperator is a Business AI Operator, a category-leader that unifies WhatsApp, Calls, and AI-powered chat & voice bots into one intelligent business communication platform. Unlike fragmented communication tools, MyOperator combines automation, intelligence, and workflow integration to help businesses run WhatsApp campaigns, manage calls, deploy AI chatbots, and track performance — all from a single, no-code platform. Trusted by 12,000+ brands including Amazon, Domino's, Apollo, and Razorpay, MyOperator enables faster responses, higher resolution rates, and scalable customer engagement — without fragmented tools or increased headcount

Role Summary

We’re hiring a Front Deployed Engineer (FDE)—a customer-facing, field-deployed engineer who owns the end-to-end delivery of AI bots/agents.

This role is “frontline”: you’ll work directly with customers (often onsite), translate business reality into bot workflows, do prompt engineering + knowledge grounding, ship deployments, and iterate until it works reliably in production.

Think: solutions engineer + implementation engineer + prompt engineer, with a strong bias for execution.

Responsibilities-

Requirement Discovery & Stakeholder Interaction

• Join customer calls alongside Sales and Revenue teams.
• Ask targeted questions to understand business objectives, user journeys, automation expectations, and edge cases.
• Identify data sources (CRM, APIs, Excel, SharePoint, etc.) required for the solution.
• Act as the AI subject-matter expert during client discussions.

Use Case & Solution Documentation

• Convert discussions into clear, structured use case documents, including:
• Problem statement & goals.
• Current vs. proposed conversational flows.
• Chatbot conversation logic, integrations, and dependencies.
• Assumptions, limitations, and success criteria.

Customer Delivery Ownership

• Own deployment of AI bots for customer use-cases (lead qualification, support, booking, etc.). Run workshops to capture processes, FAQs, edge cases, and success metrics. Drive the go-live process: requirements through monitoring and improvement.

Prompt Engineering & Conversation Design

• Craft prompts, tool instructions, guardrails, fallbacks, and escalation policies for stable behavior. Build structured conversational flows: intents, entities, routing, handoff, and compliant responses. Create reusable prompt patterns and "prompt packs."

Testing, Debugging & Iteration

• Analyze logs to find failure modes (misclassification, hallucination, poor handling). Create test sets ("golden conversations"), run regressions, and measure improvements. Coordinate with Product/Engineering for platform needs.

Integrations & Technical Coordination

• Integrate bots with APIs/webhooks (CRM, ticketing, internal tools) to complete workflows. Troubleshoot production issues and coordinate fixes/root-cause analysis.

What Success Looks Like

• Customer bots go live quickly and show high containment + high task completion with low escalation.
• You can diagnose failures from transcripts/logs and fix them with prompt/workflow/knowledge changes.
• Customers trust you as the “AI delivery owner”—clear communication, realistic timelines, crisp execution.

Requirements (Must Have)

• 2–5 years in customer-facing delivery roles: implementation, solutions engineering, customer success engineering, or similar.
• Hands-on comfort with LLMs and prompt engineering (structured outputs, guardrails, tool use, iteration).
• Strong communication: workshops, requirement capture, crisp documentation, stakeholder management.
• Technical fluency: APIs/webhooks concepts, JSON, debugging logs, basic integration troubleshooting.
• Willingness to be front deployed (customer calls/visits as needed).

Good to Have (Nice to Have)

• Experience with chatbots/voicebots, IVR, WhatsApp automation, conversational AI platforms with at least a couple of projects. 
• Understanding of metrics like containment, resolution rate, response latency, CSAT drivers.
• Prior SaaS onboarding/delivery experience in mid-market or enterprises.

Working Style & Traits We Value

• High agency: you don’t wait for perfect specs—you create clarity and ship.
• Customer empathy + engineering discipline.
• Strong bias for iteration: deploy → learn → improve.
• Calm under ambiguity (real customer environments are chaotic by default).

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.

About Us

Invorto is our Voice AI product, bringing intelligent voice agents to real-world customer and operational use cases. Our voice pipeline is built in Python, running an STT → LLM → TTS architecture on top of the Pipecat framework.

This is a chance to work on hard problems in voice AI — latency, accuracy, naturalness, and reliability — building zero-to-one, owning your area end-to-end, and shipping to production at scale.

Note: This is a customer-facing role, and strong communication skills are essential.

About the Role

We're looking for a Voice AI Research Engineer to join the Invorto team and help build and continuously improve the voice AI systems that power our intelligent voice agents. This role is focused on the specialized craft of voice AI — designing evaluation and automation frameworks that ensure our STT, LLM, and TTS pipeline performs reliably in real-world, production conditions.

What You'll Do

• Design and build automated testing and quality frameworks for our STT → LLM → TTS voice pipeline, built on Pipecat
• Evaluate and benchmark STT, LLM, and TTS/ASR components on accuracy, latency, naturalness, and robustness across accents, languages, and real-world audio conditions
• Work hands-on with STT, TTS, and ASR models — fine-tuning, evaluating, and improving them for production use cases
• Identify failure modes and edge cases across the pipeline (background noise, accents, interruptions, turn-taking, latency, pipeline-stage handoffs) and build systems to catch them before production
• Collaborate closely with engineering to integrate quality checks and automation into the voice agent development lifecycle within the Pipecat-based architecture
• Research and stay current with advances in voice AI, and bring in new techniques, models, and tools to improve pipeline performance
• Work directly with customers to understand real-world voice use cases and translate them into evaluation criteria and quality benchmarks
• Partner with product and engineering to define what "production-grade quality" means for voice agents and drive the team toward it

What We're Looking For

• 4–6 years of experience, with a specialization in voice AI systems and automated quality evaluation
• Hands-on experience with STT (Speech-to-Text), TTS (Text-to-Speech), and ASR (Automatic Speech Recognition) models
• Experience designing and building automated testing/evaluation frameworks for voice or speech systems
• Strong understanding of what drives voice AI quality — accuracy, latency, naturalness, and robustness to real-world variability
• Strong programming skills in Python; familiarity with Pipecat or similar voice pipeline/orchestration frameworks is a plus
• Understanding of STT → LLM → TTS pipeline architectures and the trade-offs involved at each stage
• Research mindset — comfortable exploring new models, techniques, and tools and translating them into practical improvements
• Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and validate quality expectations

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

Title: AI Engineer - Product & Adoption Capability

Experience: 4-7 years

Location: Hyderabad

Mode of work: Hybrid

Role Summary:

P99Soft is hiring for an applied AI engineering role that also requires GTM-type capability - the ability to think about how AI tools actually get adopted by end users, not a dedicated go-to-market or marketing title. The engineer is expected to understand user workflows, spot adoption barriers, and shape how tooling gets rolled out, while remaining hands-on with applied AI work day to day.

Key Responsibilities:

• Build and support the rollout of AI-powered tools, driving awareness, onboarding, and adoption among target end users.
• Understand and map user workflows to identify where and why adoption of new AI tooling breaks down, and design solutions to close those gaps.
• Partner closely with engineering and architecture stakeholders to translate what's technically possible into what users will actually adopt and use.
• Gather and synthesize user feedback to inform product decisions and prioritization for the AI tooling roadmap.
• Apply hands-on applied AI knowledge to evaluate tool capability and limitations firsthand, rather than relying solely on engineering input.
• Communicate technical AI concepts to non-technical stakeholders in a way that drives buy-in and correct usage.

Required Experience & Skills:

• Applied, hands-on AI experience is non-negotiable - genuine exposure to building or working closely with generative/agentic AI systems, not just using AI assistants as an end user.
• Working GTM-type capability: comfort defining requirements, prioritizing based on user needs, and driving adoption of a tool - this can come from prior product exposure rather than a formal GTM title.
• Strong user empathy and the ability to identify practical adoption barriers for enterprise tools, distinct from purely technical blockers.
• Comfort operating with generative/applied AI systems (LLMs, agentic tools) as distinct from traditional data science approaches (regression, classification).
• Background can come from startup, founder, or self-taught paths — a traditional data science or enterprise pedigree is not required, provided applied AI fundamentals are genuinely strong.

Nice to Have:

• Some depth in AI systems internals (e.g., exposure to debugging model-serving or library/version compatibility issues) is a plus, though this role does not require building custom training pipelines from scratch.
• Experience operating in a regulated, quality-driven, or highly technical enterprise environment.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health insurance.
• Paid time off and flexible working hours.
• Professional development opportunities and support for continuing education.
• Udemy Learning Licenses to enhance skills and stay up-to-date with the latest technology.

P99Soft is an Equal-Opportunity Employer

P99soft is an equal-opportunity employer. At P99soft, we are committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status, or any other special status. We stand against the discrimination of employees and individuals and are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the designated roles and responsibilities.

Life @ P99Soft

At P99soft, we believe in creating a work environment that balances professional excellence with personal well-being. Our vibrant office culture is built on mutual respect, inclusivity, and a shared passion for innovation. We host regular team-building activities, workshops, and social events to foster a sense of community and collaboration among our employees. Join us and be part of a team that values your contributions and supports your growth.

About Us

P99soft is a leading IT Services and IT Consulting company dedicated to making our customers' business operations seamless by providing them with digital services and applications using the latest technologies. We are committed to bringing excellence to all our creations. We need passion, empathy, and being customer-focused to achieve technical excellence. We believe in transparency through open communication and work with honesty and integrity while dealing with our customers and partners.

Our Vision: “To lead digital transformation for our customers, delighting them at every step, while empowering our employees and fostering success.”

Our Mission: “To attain our objectives within a framework of integrity, transparency, and respect for our clients, employees, partners, and the community, fostering mutual trust and sustainable growth.”

Journey towards digital transformations begins here. Our talented teams help you make informed decisions, enhance operation efficiencies, create state-of-the-art visual interfaces, and design dynamic workflows to bring a better customer experience. Our engineering teams take complete ownership of assigning the right talent and architecting solutions using the latest technologies.

We're building the AI operating system for the $600B global managed IT market.

Managed service providers (MSPs) run IT for lots of small and mid-sized businesses. Their technicians spend most of the day on repetitive tickets — setting up new joiners, sharing folders, fixing sign-in issues. Our first product is an AI service desk. It learns how each MSP works, turns a ticket into a plan of exact steps, and runs only what a technician approves.

Our vision is to build additional products for other parts of the MSP's business (such as voice AI, business operations and analytics), turning this into the one AI operating layer for the MSP business.

We've just raised a $4.4M pre-seed from Seedcamp, Futurepresent and Entree Capital. Our founders previously built upGrad ($2B) and Kapiva ($250M), and come from Bain Capital, Parthenon, and Morgan Stanley. Our co-founders both studied CS at IIT Delhi.

We're building a small team with very high talent density in Mumbai — people from IIT Bombay, Yale, Rippling and more.

The role:

We're hiring our first Product Designer — someone who will shape how the product looks, feels, and works from the ground up.

The hardest design problem we have is trust. A technician needs to feel comfortable letting AI make changes in a customer's Microsoft 365 or Google Workspace. So every screen needs to make it very clear what the AI knows, what it plans to do, and what it changed — and still be fast enough that a busy service desk actually uses it.

You'll work directly with the co-founder who leads product and our engineers, and own design end to end — from customer calls to shipped product.

What you'll do:

• Own the product experience end to end. Take problems from a first customer conversation to rough sketches, prototypes, and polished UI that ships — then keep improving it once it's live.
• Design how people and AI work together. Decide how the product explains what it knows, asks for approval, shows its progress, and owns up when something goes wrong. Make it easy for a technician to say yes with confidence.
• Make complex work feel simple. IT work is detailed and technical. You'll turn it into clear, fast experiences that busy teams can use without training.
• Stay close to customers. Join customer calls, watch technicians at work, test ideas with them every week, and bring what you learn straight into the product.
• Prototype fast, ideally in code. Use AI and design tools (Claude, Figma and others) to build working prototypes, so we learn from real use rather than static mockups.
• Design everywhere the product shows up — the app, integrations with tools technicians already use, operational dashboards and more.
• Build a lean design system. Give our engineers the building blocks to ship consistent UI without waiting on you.
• Set the bar for design. As our first designer, you'll shape how design is done here — the standard of quality, how we work, and who we hire next.

A few problems you might pick up in your first months: a single approval to set up 50 new joiners, with a clear "48 done, 2 need attention — and why"; a way for teams to see what the AI has learnt about each client, where it came from, and how to undo it; and a simple view that tells an owner the AI is working.

What we're looking for:

• Great product design work you've actually shipped. Consumer or B2B doesn't matter — we care much more about how you think than where you've worked.
• Strong craft and taste. Simple, clean and fast over flashy — think Linear, not a design studio website.
• Comfort going deep on a complex subject. You'll need to learn how things like Microsoft 365 groups and licences work, and enjoy doing it.
• Speed. You prototype in code or with AI tools and get ideas in front of users quickly.
• You use AI every day. You have opinions on what makes AI products feel trustworthy — and what makes them feel risky.
• High ownership and clear writing. You can take a messy problem all the way to something shipped, and explain your thinking simply along the way.

Nice to have:

• You've designed AI or agent products before.
• Early-stage startup or founder experience.
• You can write front-end code (React / Tailwind).

Probably not the right fit if

• Most of your work is brand, marketing, or research.
• You need a detailed spec and a design manager to do your best work.

Why join us?

• Real ownership. We're very early, so you'll shape how design works here — not inherit someone else's system.
• A hard, new problem. AI that takes real actions on real systems is still being figured out. You'll help define what good looks like.
• Fast impact. You'll work directly with the founders and see your work in customers' hands within weeks.

Product Engineer — Role Summary

We are looking for a Product Engineer to build user-facing products that combine AI capabilities with practical applications. You will work at the intersection of software engineering and AI, developing autonomous, agent-driven systems that solve complex educational and research problems.

Key Responsibilities:

• Product Development: Design, build, and deploy production-ready applications powered by LLMs and AI agents.
• Data Engineering: Build scalable ETL/ELT pipelines to process structured and unstructured data, including text and audio, for RAG and model fine-tuning.
• Agentic Workflows: Develop multi-step AI agents with tool calling, APIs, databases, search, reasoning, and memory.
• Rapid Prototyping: Turn ideas and research concepts into interactive, production-ready applications.
• AI Integration: Use frameworks such as LangChain, LlamaIndex, AutoGen, or custom orchestrators to integrate AI into scalable systems.
• User Experience: Transform raw AI outputs into reliable, intuitive, and responsive user experiences.
• Collaboration: Work closely with ML researchers and data engineers to integrate custom and fine-tuned models.
• Observability: Monitor agent behavior, manage edge cases, reduce hallucinations, and improve reliability in production.

The ideal candidate combines strong software engineering, AI/LLM expertise, data engineering, and product thinking, with the ability to take an AI concept from prototype to production.

Strong Product Designer from top college profile

2

Mandatory (Experience) - Minimum 2+ YOE in UX / Product Design, with strong focus on B2C Products

3

Mandatory (Portfolio) - Strong portfolio of UX / Product Design works for top / high-traffic B2C Products

4

Mandatory (Company): Top B2C product company

5

Mandatory (Education) - Must have Design Education (BDes, MDes) from Tier1 college (NIT, NIFT. IIT). Tier2 colleges will be given 2nd priority

6

Mandatory (Exclusion) - Only UX designer wont work, we need product designers

7

Mandatory (Age)—The candidate's age should be below 28 years

8

Preferred (Experience) - Must have design system, AI product design, conversational design keywords

Role Overview

We are looking for an experienced professional to evaluate AI-generated responses for conversational AI agents used in travel-related products. The role focuses on assessing response accuracy, relevance, completeness, and quality to improve AI performance.

Key Responsibilities

• Evaluate AI-generated responses against predefined guidelines and quality standards.
• Perform data annotation, labeling, classification, and quality reviews.
• Identify incorrect, misleading, irrelevant, or incomplete responses and potential AI hallucinations.
• Analyze evaluation data to identify recurring errors, quality gaps, and improvement opportunities.
• Track quality metrics, document findings, and recommend improvements.
• Use Excel/Google Sheets and basic SQL, where applicable, to analyze evaluation data.
• Collaborate with AI and Machine Learning teams to improve conversational AI performance.

Required Skills

• 5–8 years of experience in Data Annotation, AI Evaluation, Content Quality, Search Relevance, or Quality Assurance.
• Strong analytical, problem-solving, and attention-to-detail skills.
• Experience applying evaluation guidelines and quality standards consistently.
• Proficiency in Excel or Google Sheets.
• Good written communication and documentation skills.
• Understanding of quality metrics and data analysis.

Good to Have

• Exposure to Generative AI, LLMs, conversational AI, or AI response evaluation.
• Experience with Human-in-the-Loop (HITL), AI training data validation, or hallucination detection.
• Basic SQL knowledge.
• Experience in travel, hospitality, or search quality evaluation.