Solutions Architect

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.

As a Solutions Engineer/Sales Engineer, you will act as a trusted technical advisor to prospective customers in the US market. You will own the technical evaluation journey end-to-end, from the first discovery call to closing the deal, by demonstrating how our platform solves real-world data integration challenges. This role involves working closely with global customers (primarily North America ), designing scalable architectures, running tailored product demos, and building proofs-of-concept that showcase value.

Responsibilities:

• Run technical discovery calls with Heads of Data, Data Engineering Managers, and CTOs to understand their stack, pain points, and constraints. These are global conversations, primarily with customers in North America and Europe, and you will own them end-to-end.
• Design and present reference architectures showing how Hevo fits into their existing data stack (e. g., Salesforce, Postgres, GA4 Snowflake, dbt).
• Run live product demos tailored to the customer's stack. These are not scripted walkthroughs. You will need to read the room, adapt on the fly, and handle unexpected technical questions with confidence.
• Own the technical evaluation from the first conversation to the closed deal by addressing deep technical questions and earning trust with engineering teams.
• Build proofs-of-concept by configuring real pipelines from source systems (Salesforce, Outreach, Postgres, MySQL) into destinations like Snowflake or BigQuery.
• Develop deep expertise in the data integration landscape, including native solutions from AWS, GCP, and Azure (AWS Glue, Azure Data Factory, Google Cloud Dataflow) as well as other data pipeline and integration platforms, and articulate Hevo's technical advantages in a way that lands with both technical and non-technical buyers.
• Partner with Account Executives to drive technical wins and with Customer Success to ensure smooth handoffs after a deal closes.
• Share customer feedback and patterns with Product and Engineering to influence the roadmap.

Requirements:

• 2 to 6 years of hands-on experience as a Data engineer, Analytics engineer, ETL/ELT developer, or Data warehouse engineer.
• Experience building and operating real data pipelines in production, including handling source schema changes, failures, and reliability issues.
• Strong fundamentals in SQL and at least one cloud data warehouse (Snowflake, BigQuery, or Redshift).
• Experience with at least one orchestration or transformation tool (Airflow, dbt, or similar).
• Exceptional communication and presentation skills.
• This is non-negotiable. You will be the face of Hevo's technical capability to a global customer base. That means:
• Your spoken English is clear, confident, and easy to follow for an international audience.
• You are comfortable presenting to groups of 5 to 15 people, including senior technical leaders, over video calls.
• You can structure a technical narrative, not just answer questions but guide a conversation toward the right conclusion.
• You can hold your own when a customer pushes back or challenges your recommendation.
• You have presented or demoed something technical to an audience before, in any context: internal reviews, client calls, meetups, or conferences.
• Genuine interest in customer-facing work, even if you have not done it formally before.

Good to have:

• Experience with CDC tools or data integration platforms, whether cloud-native (AWS Glue, Azure Data Factory, or Google Cloud Dataflow) or third-party pipeline and integration tools.
• Exposure to multiple source system types such as CRMs, ad platforms, SaaS APIs, and OLTP databases.
• Public technical writing, conference talks, or open-source contributions.
• Prior experience in customer conversations, even informally. For example, presenting to internal stakeholders or analytics teams or working with international teams across time zones.

About the Role

We are looking for a dynamic and customer-focused Presales Engineer – Cloud & AI to support our Cloud Transformation, Modernization, Managed Services, and AI/GenAI practices.

This role is pivotal in shaping technical solutions for prospective customers, driving value-based conversations, and bridging the gap between customer challenges and Comprinno's cloud and AI capabilities.

As a Presales Engineer – Cloud & AI, you will work closely with Sales, Solution Architects, Data & AI teams, and Delivery teams to understand customer requirements, design high-level solutions, and articulate how Comprinno's offerings can accelerate digital transformation and business outcomes.

This is a high-impact role that combines cloud solutioning, technical consulting, AI awareness, customer engagement, and presales excellence.

Key Responsibilities

Customer Discovery & Solutioning

• Engage with prospective customers to understand business objectives, technical challenges, and transformation goals.
• Conduct discovery workshops, assessments, and technical discussions to identify cloud and AI opportunities.
• Translate business requirements into high-level cloud and AI solution architectures.
• Collaborate with Solution Architects and technical teams to develop scalable and cost-effective solutions.

Cloud Transformation Consulting

• Support customer initiatives across:
• Cloud Migration
• Application Modernization
• DevOps Transformation
• Managed Services
• Security & Compliance
• Resilience & Disaster Recovery
• Conduct cloud assessments and migration readiness evaluations.
• Prepare cloud cost estimates, modernization roadmaps, and optimization recommendations.
• Leverage AWS programs and frameworks such as:
• Migration Acceleration Program (MAP)
• AWS Well-Architected Framework (WAFR)
• Foundational Technical Review (FTR)

AI & GenAI Solution Consulting

• Identify opportunities for AI, GenAI, and Agentic AI adoption within customer environments.
• Participate in AI discovery workshops and business value discussions.
• Support solution design for AI-powered applications leveraging AWS AI services.
• Collaborate with Data & AI teams to position analytics, machine learning, and Generative AI offerings.
• Assist customers in identifying suitable use cases for:
• Generative AI
• AI Assistants
• Knowledge Management Solutions
• Intelligent Automation
• Conversational AI

Proposal Development & Technical Presales

• Collaborate with Solution Architects to create:
• Technical Proposals
• Architecture Diagrams
• Effort Estimates
• Statements of Work (SOWs)
• Technical Responses to RFPs/RFIs
• Present solutions, recommendations, and technical approaches to customer stakeholders.
• Support Proof of Concepts (PoCs), demonstrations, and technical validations.
• Participate in technical reviews and solution walkthroughs.

Customer Engagement & Thought Leadership

• Attend customer meetings jointly with Sales teams to provide technical expertise.
• Build credibility and trust with customer technical and business stakeholders.
• Contribute to webinars, workshops, technical presentations, and customer-facing events.
• Write blogs, case studies, solution briefs, and technical content that supports business growth.
• Maintain an active presence in cloud and AI communities.

Collaboration & Knowledge Management

• Collaborate with Delivery teams to ensure smooth handover and alignment between presales and execution.
• Maintain reusable presales assets, templates, assessment frameworks, and knowledge repositories.
• Continuously stay updated on AWS services, AI advancements, partner programs, and emerging technology trends.
• Contribute to internal capability building and knowledge-sharing initiatives.

Travel & Customer Interaction

• Travel as required for customer meetings, workshops, assessments, events, and strategic engagements.
• Represent Comprinno professionally during all customer-facing interactions.

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 3–5 years of experience in Presales, Solution Consulting, Cloud Consulting, Technical Sales, or related customer-facing roles.
• Strong understanding of AWS cloud services across:
• Compute
• Networking
• Storage
• Security
• Databases
• Knowledge of cloud migration and modernization frameworks such as AWS MAP.
• Familiarity with AWS cloud assessment tools including Migration Evaluator and AWS Well-Architected Tool.
• Understanding of:
• Kubernetes
• Containerization
• Cloud-Native Architectures
• DevOps Practices
• Hands-on exposure to Infrastructure as Code using Terraform or CloudFormation.
• Ability to create:
• Solution Documents
• Architecture Diagrams
• Technical Proposals
• Effort Estimates
• Statements of Work
• Understanding of Generative AI concepts including:
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Assistants
• Agentic AI Concepts
• Familiarity with AWS AI services such as:
• Amazon Bedrock
• Amazon SageMaker
• Amazon Q
• AWS Solutions Architect – Professional Certification.
• Experience positioning AI, GenAI, Analytics, or Data Engineering solutions.
• Familiarity with AI frameworks such as:
• LangChain
• LangGraph
• CrewAI
• OpenAI APIs
• Anthropic APIs
• Strong communication, presentation, and stakeholder management skills.
• Experience conducting AI assessments, GenAI workshops, or AI proof-of-concepts.
• Experience contributing to webinars, blogs, case studies, or technical marketing content.
• AWS Solutions Architect – Associate Certification (Mandatory).
• Customer-centric mindset with strong problem-solving abilities.

Desired Qualifications & Skills

• AWS Specialty Certifications such as:
• Security Specialty
• Advanced Networking Specialty
• Machine Learning Specialty
• DevOps Engineer Professional
• Understanding of compliance frameworks such as:
• ISO 27001
• SOC 2
• HIPAA
• MBA or equivalent business qualification.
• Contributions to industry blogs, webinars, conferences, technical communities, or open-source initiatives.

What We're Looking For

• Strong consulting mindset with the ability to understand customer business challenges.
• Excellent communication and presentation skills.
• Ability to balance technical depth with business value articulation.
• Passion for cloud technologies, AI, and emerging innovation.
• Collaborative team player who can work across Sales, Architecture, Delivery, and Product teams.
• High ownership and accountability.
• Curiosity and continuous learning mindset.
• Willingness to travel and work from customer locations across India and internationally as required by project engagements.

What Success Looks Like

• Consistently contributes to qualified pipeline creation and deal progression.
• Produces high-quality proposals, architecture recommendations, assessments, and Statements of Work.
• Builds credibility with customers through strong technical consulting and solution design.
• Successfully supports closure of Migration, Modernization, Managed Services, Security, and AI opportunities.
• Develops reusable presales assets, assessment frameworks, and solution accelerators.
• Contributes to thought leadership through blogs, webinars, technical presentations, and customer-facing content.
• Continuously expands expertise in AWS, Cloud, AI, and emerging technologies.

Why Join Comprinno

• Work at the forefront of Cloud, AI, and AWS innovation with one of the leading AWS Partners in APJ.
• Be part of real transformation initiatives involving Migration, Modernization, DevOps, Security, Managed Services, and Generative AI.
• Collaborate directly with enterprise customers and influence strategic technology decisions.
• Accelerate your growth through AWS certifications, mentorship, and hands-on customer engagements.
• Contribute to innovative solutions including Tevico and future AI-powered offerings.
• Build thought leadership through webinars, blogs, events, and community participation.
• Join a collaborative, high-performance culture that values ownership, innovation, and continuous learning.

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.

Software Engineer

Company Summary :

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com

Business Summary :

The Deltek Engineering and Technology team builds best-in-class solutions to delight customers and meet their business needs. We are laser-focused on software design, development, innovation and quality. Our team of experts has the talent, skills and values to deliver products and services that are easy to use, reliable, sustainable and competitive. If you're looking for a safe environment where ideas are welcome, growth is supported and questions are encouraged – consider joining us as we explore the limitless opportunities of the software industry.

Position Responsibilities:

• Collaborate with the development team to maintain, enhance, and scale the product for enterprise use.
• Design and develop scalable, high-performance solutions using cloud technologies and containerization.
• Contribute to all phases of the development lifecycle, following SOLID principles and best practices.
• Write well-designed, testable, and efficient code with a strong emphasis on Test-Driven Development (TDD), ensuring comprehensive unit, integration, and performance testing.
• Ensure software designs comply with specifications and security best practices.
• Contribute ideas to improve application maintainability and performance under the guidance of senior engineers.

AI-Specific Responsibilities:

• Integrate AI-powered tools and frameworks to enhance code quality and development efficiency.
• Utilize AI-driven analytics to identify performance bottlenecks and optimize system performance.
• Implement AI-based security measures to proactively detect and mitigate potential threats.
• Leverage AI for automated testing and continuous integration/continuous deployment (CI/CD) processes.
• Support the adoption and effective use of AI agents for automating repetitive development, deployment, and testing processes within the engineering team.

Qualifications :

• 2-3 years of software engineering experience, including at least 1 year of hands-on AI/ML experience.
• Proficient in Node.js and TypeScript/React development, with experience in React 18+, Hooks (useState, useEffect, useContext), and WebSocket clients.
• Strong full-stack development experience with modern web technologies.
• Experience with ASP.NET Core (C#) is good to have.
• Experience developing REST APIs.
• Proficiency in front-end technologies (JavaScript, HTML, CSS, Bootstrap, and UI frameworks).
• Strong knowledge of cloud platforms (AWS preferred), including scalability and enterprise cloud. 
• Experience with security best practices in web and API development.
• Experience with Test-Driven Development (TDD).
• Strong database experience, focused on query optimization 
• Strong analytical skills, problem-solving abilities, and curiosity to explore new technologies.
• Ability to communicate effectively, including explaining technical concepts to non-technical stakeholders.
• High commitment to continuous learning, innovation, and improvement.

AI-Specific Qualifications:

• Practical experience with prompt engineering and LLM response optimization
• Knowledge of AI-driven development tools and platforms such as Claude Code, GitHub Copilot in Agentic Mode.
• Knowledge of AI-based security protocols and threat detection systems.
• Experience integrating GenAI or Agentic AI agents into full-stack workflows (e.g., using AI for code reviews, automated bug fixes, or system monitoring).
• Demonstrated proficiency with AI-assisted development tools and prompt engineering for code generation, testing, or documentation.

Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World's Best Employers 2025) is consistently listed among the most admired companies in the world. 

This role is part of Cognizant IOA (Intuitive Operations and Automation) — and more specifically, a product team with its own origin story. We started as Matterway, a German startup building automation software from scratch. We were acquired by Cognizant, but we kept our team, our culture, our pace, and our way of working. We move like a startup, think like a startup, and now do it with the backing of a global company. 

We combine human expertise with intelligent automation, ML operations, and digital experience solutions to help technology and digital-native companies build smarter, more adaptive operating models. 

What's the opportunity? 

We are looking for Senior Product Engineers to join our team. We're a tight crew of 5 senior engineers, from different corners of the world. We're hiring 3 more people, and those people will shape what this team becomes. 

We're building a platform to support the agentification of our operations. You'll work across a suite of products including a cloud platform for process optimization, desktop application, browser extension, and specialized AI agents. 

This is genuinely frontier work: we don't follow AI trends, we implement them. New model drops on a Monday; we've prototyped with it by Wednesday. 

We believe this is the most exciting time to join. Be part of the founding R&D talent in this area and help set the technical bar for everything that comes next. 

What will you be doing? 

Your day-to-day responsibilities: 

• Design and evolve the core architecture of our platform 
• Set technical standards and take ownership of complex projects end-to-end 
• Work on a well-architected, fast-evolving TypeScript codebase using technologies such as React, Node.js, Electron, and GraphQL 
• Collaborate with product managers, designers, and engineers to solve challenging technical and business problems, with real autonomy 
• Participate in the full development lifecycle: scoping, design, estimation, coding, testing, debugging, code reviews, maintenance, and support 
• Evaluate and implement proofs of concept using the latest AI tools and models 

You will know you're successful if: 

• You develop projects independently until they deliver their intended business value 
• You keep top-notch software quality standards about design, implementation, and documentation 
• You're the person who brings something new to the team's radar, a model, a technique, a tool, before anyone else has heard of it 

What makes you a great fit 

Must-haves: 

• Excellent English (C1+) with exceptional written and verbal communication 
• Strong proficiency with TypeScript across frontend and backend, including building and maintaining Node.js-based services 
• Experience in frontend development using modern frameworks such as Vue.js or React 
• Knowledge of any E2E testing framework such as Playwright, Puppeteer, Selenium, Cypress 
• Ability to work independently and take ownership of deliverables 
• Strong technical fundamentals, genuine intellectual curiosity, and a drive to keep getting better 
• You follow AI closely, not just as a user but as someone who reads the papers, watches the releases, and has opinions. You're excited about where this is going and want to be building at the edge of it 

Nice-to-haves: 

• Familiarity with AI-coding tooling (Claude Code, Cursor, OpenCode, etc.) 
• Experience with cloud infrastructure (AWS, Azure or GCP) and infra-as-code deployment 
• Having built or maintained CI/CD pipelines or workflows, especially GitHub actions 

Why join us? 

• Be at the cutting edge of AI agents and applying LLMs to real-world use cases, not in theory but in production 
• Work on hard problems with high agency: your ideas get heard; your decisions get shipped 
• Join a small but growing internationally distributed team. 
• giving you real influence over how it evolves 
• The resources of a global company with the speed and culture of a startup 
• Remote-first set-up, with the option to work from one of our 13 locations in India: Chennai, Bangalore, Hyderabad, Pune, Mumbai, Gurgaon, Noida, Kolkata, Kochi, Coimbatore, Bhubaneswar, Mangalore, and Indore 
• Flexible working hours 
• Collaborative, pragmatic engineering culture focused on outcomes 
• Fast-growing team within Cognizant, with access to global resources and real career opportunities 

Role Description

Software Engineer is a full-time role based in Hyderabad with Onsite work arrangement. This role involves designing, developing, and maintaining back-end services and APIs, ensuring high performance, scalability, and security across platforms. The engineer will participate in architecture discussions, code reviews, and technical decision-making, collaborating closely with product owners, QA, and cross-functional teams. Daily responsibilities include writing clean, maintainable code, troubleshooting complex issues, improving system performance, and contributing to best practices, documentation, and engineering standards. The role also includes mentoring less experienced engineers and supporting continuous improvement in development processes and tooling.

Key Requirements/Skills

4-7 years of overall experience in software development with strong expertise in building scalable web & mobile applications.

• Strong technical decision-making ability, including architecture design, technology selection and implementation of best practices.
• Front-end expertise: Strong experience in React, JavaScript, TypeScript, NextJS and building responsive and user-friendly UI/UX.
• Back-end development: Hands-on experience with Node.js, Express JS, Nest JS, RESTful APIs, API design, and server-side architecture.
• Databases : Good Hands on Exprience in both SQL(PostgreSQL Preferred) & No SQL Databases
• Gen AI Expertise: Experience in building RAG & LLM Systems, implementing AI/ML models and integrating AI-based solutions to solve business problems. Expereince with Langchain, langgraph and Vector DBs, Voice AI(STT, TTS) Models and experience in using Open AI Tools (Calude, Cursor, etc.)
• Cloud & DevOps exposure: Experience with AWS/Azure, understanding of CI/CD pipelines, and cloud-based deployments.
• Code quality & best practices: Experience in code reviews, Git version control, and ensuring maintainable and secure code.
• Team leadership: Ability to mentor developers, guide technical discussions, and collaborate across teams.
• Strong communication skills to effectively interact with technical and non-technical stakeholders.
• Experience working in high-compliance environments such as healthcare systems is a plus.
• Certifications in AWS & Other skills and technologies will be an added advantage.

Educational Qualification

• B.Tech / M.Tech in CSE/IT/AI&ML only from a recognized university/college. 

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).

AI Solution Architect

Experience: 12+ Years

Location: Coimbatore / Hybrid

Joining: Immediate / Within 30 Days

Primary Skills: Enterprise Architecture, Python, REST APIs, Microservices, Distributed Systems, Cloud (AWS/Azure/GCP), CI/CD, Docker, Kubernetes, Enterprise Data Architecture, Integration Patterns.

Preferred Skills: LLM Integrations, RAG Pipelines, AI Agents, Agentic Workflows, MCP (Model Context Protocol), Vector Databases, Prompt Engineering, LangChain/LlamaIndex, LLMOps, Multi-Agent Orchestration.

About the Role

At Techjays, we're helping companies reimagine how they build, operate, and scale with AI at the core. We focus on building secure, scalable, production-grade AI systems that solve real business problems and deliver measurable outcomes.

We're looking for an AI Solution Architect who can own enterprise-level solution architecture end-to-end. The ideal candidate combines deep technical expertise with the ability to understand complex business challenges, engage with prospective clients, and design compelling, scalable, AI-native solutions.

This is a senior technical role at the intersection of enterprise architecture, pre-sales, solutioning, and delivery governance. You'll collaborate with leadership, engineering teams, and clients to architect solutions spanning AI integrations, RAG pipelines, agentic workflows, cloud infrastructure, and enterprise platforms.

This role requires a strong technical background and current hands-on expertise. Candidates with purely pre-sales experience or non-technical solutioning backgrounds will not be a fit.

Key Responsibilities

• Own end-to-end enterprise architecture for AI-native platforms, defining high-level and low-level designs across backend systems, data platforms, and AI components.
• Lead solutioning for complex enterprise engagements, translating client requirements into technically sound, secure, scalable, and commercially viable architectures.
• Define reference architectures and design standards for LLM integrations, RAG pipelines, agentic workflows, MCP-based integrations, and enterprise data platforms.
• Partner with pre-sales and business development teams to prepare RFP responses, technical proposals, solution presentations, and architecture documents.
• Lead client discovery sessions and technical presentations, communicating architectural decisions and trade-offs to technical and executive stakeholders.
• Conduct architecture reviews and technical assessments to ensure scalability

Read This Before Anything Else

We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.

About CraftMyPlate

CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.

Where We Stand

Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.

Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.

The Technical Reality

Here's an honest read of the engineering problem, not a sanitized version of it.

Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.

Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.

The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.

You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.

Why This Role Exists

You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.

If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.

What You'll Own

• Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
• Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
• The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
• The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
• Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
• Technical accountability. When something breaks, you fix it. You don't escalate and wait.

Our Stack, and the Depth We Expect

Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.

Go deep here. This is where the real architecture decisions live, and where the business impact is highest:

• AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
• TypeScript, our primary language across backend and frontend.
• Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.

Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.

This Is You If

• You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
• You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
• You've made engineers around you measurably better, whether or not you've held the title for it yet.
• You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
• You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
• You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.

This Might Not Be the Right Fit If

• You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
• You'd rather receive direction than bring us architecture and AI strategy yourself.
• You haven't yet gotten hands-on with AI coding tools in your daily work.
• You're drawn more to the title than the work behind it.

If none of that sounds like you, we'd love to hear from you.

Requirements

• 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
• Prior experience leading or mentoring engineers, formally or informally.
• Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
• Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.

Compensation

Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.

If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.