Hands‑on Tech Lead / Founding Engineer

Shivalik Design Pvt Ltd — GOTS-certified garment export house in Faridabad, Haryana, manufacturing for UK/EU brands. We are hiring for a full-time, on-site role in Faridabad.

About the role:

We are building AI-driven automation across our factory and export operations. As AI Automation Lead (Operations), you will design, build, and own AI/automation workflows that connect our ERP, WhatsApp, Google Sheets, and email — and roll them out across production, quality, merchandising, and logistics.

Responsibilities:

- Design and deploy automation workflows across ERP, WhatsApp Business, Google Sheets/Drive, and email.

- Build and maintain LLM-powered agents for document processing, query handling, status updates, and reporting.

- Own the automation backlog for factory operations: production planning, dispatch tracking, sample approvals, QC, inventory, and shipping documentation.

- Integrate internal systems (ERP, PLM, messaging) via APIs, webhooks, and low-code platforms.

- Set standards, document flows, train operations staff, and measure impact (time saved, error rate, throughput).

- Collaborate with IT and operations leadership on data, security, and scaling.

Requirements:

- 3–5 years experience with n8n, Make (Integromat), Python, and LLM agents.

- Hands-on automation across ERPs, WhatsApp Business API, Google Workspace (Sheets, Drive, Gmail, Calendar), and email workflows.

- Strong Python; comfort building REST API connectors, webhooks, and scheduled jobs.

- Experience prompting, fine-tuning, or orchestrating LLMs (OpenAI, Anthropic, Gemini, open-source) into agentic workflows.

- Comfort working on-site with factory/operations teams and translating business needs into automation.

Nice to have:

- Garment/apparels/exports domain experience.

- Experience with SAP, Oracle, Tally, Zoho, or similar ERPs.

- Knowledge of OCR, document extraction, and structured data pipelines.

Compensation: ₹14–24 LPA, full-time, on-site at Faridabad (Haryana).

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: Tech Lead / Engineering Lead

Experience: 8-10 years

Location: Sector 55, Gurugram (On-site, 5 days)

Industry: B2B SaaS / Enterprise Technology

About Master-O:

Master-O is a sales enablement platform used by leading enterprises across industries like FMCG, Pharma, Banking, Insurance, Automotive, Retail, Technology etc. to drive the capability development and frontline readiness for their customer-facing teams with the help of microlearning, game-based assessments and AI-powered conversational roleplays.

As we continue to expand our enterprise deployments across Pan India, North America, Middle East, and Southeast Asia, we are looking for a Tech Lead to take ownership of our engineering function and drive the successful delivery, implementation, and scalability of our solution.

The Role:

This is a high-ownership role for someone who enjoys building features, solving complex engineering problems, and collaborating with internal teams and customers. You will be leading a team of 5–6 developers and will be the face of the engineering function at Master-O.

Reporting directly to the Founder, this role requires someone who can balance engineering excellence with business priorities and ensure reliable delivery across multiple enterprise clients and geographies.

We are particularly interested in people who have prior worked in a growing SaaS organisation or have entrepreneurial experience and understand what it takes to build and deliver features from scratch.

Key Responsibilities:

1. Engineering Leadership & Technical Ownership

• Own the engineering function, including architecture, development, code quality, performance, scalability, security, and maintenance.
• Lead a team of 5-6 engineers, providing technical direction, reviewing code, ensuring timely delivery and nurturing their career path.
• Remain hands-on with development and debugging rather than functioning solely as a people manager.
• Establish engineering standards, development practices, testing protocols, and release processes.
• Make pragmatic technology decisions that balance long-term scalability with ad-hoc  business requirements.

2. Enterprise Implementations & Client Delivery

• Own the technical execution of our implementations with enterprise clients across the globe.
• Drive client-specific configurations, integrations, customizations, deployments, and production rollouts.
• Work closely with the Founder, Customer Success team, Product team, and other key stakeholders to translate client requirements into robust technical outcomes.
• Troubleshoot complex production issues, manage technical dependencies within team, and ensure implementation timelines and quality standards are met.
• Build reusable frameworks and integration capabilities that reduce implementation time and minimize repetitive custom development.

3. AI Engineering & Emerging Technologies

• Evaluate and implement AI capabilities that solve real enterprise problems and enhance product functionality.
• Experience integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents into enterprise applications will be a strong advantage.
• Understand the practical considerations of deploying AI in production, including data security, reliability, latency, cost, and evaluation.
• Encourage responsible adoption of AI coding tools such as Claude Code while ensuring engineers retain strong fundamentals, understand the code they ship, and take ownership of its quality.

4. Team & Execution Management

• Take ownership of engineering priorities, sprint execution, resource allocation, and delivery commitments.
• Build a culture of accountability, ownership, collaboration, and continuous improvement.
• Ensure the team can independently diagnose and resolve technical problems rather than relying excessively on external tools or generated code.
• Collaborate with leadership to align engineering priorities with customer commitments, product roadmaps, and business objectives.

Required Technical Skills:

• Strong hands-on experience with Node.js, Express.js, React, MySQL, Python, and AWS.
• Solid understanding of backend architecture, REST APIs, database design, system integrations, and cloud-based deployments.
• Experience building, maintaining, and scaling production-grade mobile and web applications.
• Strong debugging, code review, system design, and performance optimization skills.
• Familiarity with software development lifecycle practices, version control, automated testing, CI/CD, and production monitoring.
• Ability to make independent technical decisions and take ownership of issues from identification through resolution.

Experience & Qualifications:

• 8–10 years of relevant software engineering experience, with demonstrated progression into technical leadership.
• Prior experience leading a team of junior and mid-level engineers.
• Experience in a B2B SaaS company or an enterprise technology environment is strongly preferred.
• Experience managing enterprise client implementations, integrations, and production deployments.
• B.Tech / B.E. in Computer Science, Information Technology, or a related engineering discipline, preferably from a Tier-1 engineering college.

What We Are Looking For:

We are looking for a seasoned engineering professional who has experience handling multiple clients, varied integration requirements, competing priorities, and production issues.

You must be flexible to coordinate across time zones and work outside standard business hours when client implementations or critical releases require it.

This role offers the opportunity to work closely with the Founder, influence the product and architecture decisions, lead a compact engineering team, and directly shape how our technology scales across enterprise customers in not just domestic but international markets.

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.

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

We are a UK-based ecommerce company looking for a hands-on AI Automation & Integrations Engineer based in India to work directly with the founder.

Our goal is to progressively build an AI-first ecommerce operation by using AI, automation, APIs and software integrations to reduce manual work, improve decision-making and identify opportunities to increase revenue and profitability.

This is not a traditional data science or prompt engineering role. We are looking for a builder who can understand real business problems and turn them into reliable working systems.

What you will work on

• Build AI-powered automations and internal tools
• Connect ecommerce platforms and business systems through APIs and webhooks
• Build AI agents and LLM-powered workflows
• Automate repetitive operational processes
• Work with Shopify and ecommerce data
• Build automated reporting, alerts and business intelligence
• Develop inventory forecasting and operational tools
• Integrate AI with customer service, marketing, fulfilment and other business systems
• Identify new areas where AI and automation can improve efficiency, revenue or profitability
• Maintain and improve existing automations

Required skills

• Strong Python experience
• Strong understanding of REST APIs and webhooks
• Experience building software integrations and automations
• Practical experience using LLM APIs such as Claude, OpenAI or Gemini
• Experience working with databases such as PostgreSQL
• Git/GitHub
• Strong problem-solving ability
• Good written and spoken English
• Ability to work independently and take ownership of projects

Highly desirable

• n8n
• Shopify Admin API
• GraphQL
• JavaScript/TypeScript
• AI agents
• LangGraph/LangChain
• MCP
• AWS/GCP
• Ecommerce experience
• Data extraction/scraping
• Customer service or marketing integrations

We value real projects and practical ability more than certificates.

Candidates should be comfortable showing examples of AI automations, integrations, agents or software systems they have personally built.

Location: Remote, India

Experience: 3-7 years

Salary: ₹15-22 LPA depending on experience

• We are seeking a high-velocity Senior Technical Lead with an overall experience
• of 12+ years in software engineering who thrives in an environment of autonomy
• and rapid iteration. At Nomiso, we don't just write code; we build resilient systems.
• This role is designed for a builder who embraces our core philosophy: Build, Ship,
• Measure, Improve. You will be responsible for taking features from a raw concept
• to a live environment, ensuring that every deployment delivers high technical
• excellence and system stability. You are not just an executor; you are a technical
• owner and system architect who understands that the "Ship" is only the midpoint of the system lifecycle.

What We’re Looking For (Who You Are)

● AI Systems Architect (5+ years in AI - LLM, RAG, Context Engineering, React, Prompt): You've shipped multiple production LLM systems at scale. Deep understanding of RAG, fine-tuning, prompt optimization, inference scaling, and cost management. You make pragmatic trade-offs between

accuracy, latency, and cost.You are accountable for the high quality solution and timely shipment of the feature as per committed timeline.

● Technical Lead Manager (TLM): In this role you will do 70% technical work and 30% people management & project management work. You've led engineering teams (4-8+ engineers). You grow engineers through mentoring, clear feedback, and ownership. You balance shipping speed with technical excellence and team development.

● The "Builder" Mentality: You have a bias toward action. You prefer a

working feature over a perfect specification and understand the value of

getting software into the hands of users early. You will not leave the tech

debt for a long time. Tech debt will be continuously addressed as product matures.

● Pragmatic Architect: You choose the right tool for the job, balancing

long-term scalability with the immediate need for speed and delivery.

● Cross-functional engagement: Partner with Product, QA, and Solution

Architects, Project manager to align execution with outcomes

● Continuous Learner: You view "Improvement" as a mandatory phase, not an optional one. You are eager to refactor and pivot based on objective evidence.

Requirement

AI Expertise

• LLM APIs (OpenAI, Anthropic, Hugging Face), model selection and trade-offs. RAG pipeline architecture, fine-tuning strategies, prompt engineering, Agentic patterns, multi-step reasoning, reliability under uncertainty

Fullstack depth

● Backend: Python (FastAPI,

Django) and Node.js (Express,

Nest.js)

● Frontend: React (TypeScript,

state management, performance

optimization)

● Databases: PostgreSQL (query

optimization, schema design,

scaling)

● Infrastructure: AWS (Lambda,

ECS, RDS, S3), Docker, CI/CD,

monitoring

Leadership

● Managed engineering teams

(4-8+ engineers)

Category Requirement

● Experience mentoring and

growing engineers

● Track record of building

high-performing teams

● Comfortable with ambiguity and

rapid decision-making

Experience 12+ years in a technical-focused

engineering environment.

Education Degree in CS or equivalent professional

experience.

You will operate within a cross-functional squad, collaborating daily with Solution

Architects and other engineering peers. You will ensure that features are released

safely and frequently, and own the success of the product, by analysing the

insights and user feedback. Our hierarchy is flat; you are expected to provide

technical leadership and mentorship to junior peers while having a direct line of

communication with leadership regarding technical strategy and technical debt.

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 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).

Shivalik Design Pvt Ltd — GOTS-certified garment export house in Faridabad, Haryana, manufacturing for UK/EU brands. We are hiring for a full-time, on-site role in Faridabad.

About the role:

We are looking for an AI Automation Specialist to design and run no-code / low-code automation and AI-agent workflows that connect our factory, supply-chain and office systems.

What you'll do:

- Build automation workflows using no-code tools (n8n, Zapier, Make) and AI assistants.

- Integrate ChatGPT and Gemini APIs into recurring operational workflows (document handling, data extraction, summaries, alerts).

- Connect ERP, WhatsApp, Google Sheets, email and other tools used across factory operations.

- Own day-to-day monitoring, error-handling and iteration of automation runs.

- Translate operational requirements into working AI-agent flows and share runbooks.

What we're looking for:

- 1–3 years of hands-on no-code automation / AI-agent work.

- Practical experience with n8n, Zapier and Make.

- Working knowledge of ChatGPT and Gemini APIs and how to plug them into automation.

- Comfortable with spreadsheets, mail and WhatsApp integrations.

- Based in, or willing to relocate to, Faridabad (on-site, full-time).