Data and AI practice at NIIT · Bengaluru (Bangalore) · 5 - 15 years · ₹12L - ₹22L / yr · Posted 12 Aug 2026

Key Responsibilities
1. Solutioning & Proposal Development
• Partner with Senior SMEs and Practice Leads to design end-to-end Data & AI solutions for client pursuits — contributing to structure, content, and commercial framing.
• Build client proposals, solution documents, and program structures that are well-organized, accurate, and ready to use without significant rework.
• Translate client requirements into structured, outcome-oriented learning journeys — adoption, capability uplift, and measurable business outcomes, not just module lists.
• Support customized offerings across Data Engineering, AI / ML, and GenAI and Agentic AI tracks; help assemble pursuits from existing accelerators rather than rebuilding from scratch.
2. Client Engagement Support
• Participate in client discussions, discovery calls, and requirement-gathering sessions — capture context with the rigour that makes the next conversation sharper.
• Convert business needs into solution frameworks and delivery models with guidance from Senior SMEs; document customer priorities so Practice and Sales can act on them.
• Support pitch decks, case studies, and success stories — buyer-specific, visually clean, and aligned to how the customer thinks about their own problem.
• Stay engaged through the proposal cycle and handoff to delivery; ensure no requirement gets lost between discovery and execution.
3. Content & Program Structuring
• Assist in designing curriculum outlines, learning journeys, and hands-on lab structures that hold up against real-world enterprise contexts.
• Work with internal and external SMEs to ensure content aligns with current industry trends, real use cases, and business outcomes — not generic technology overviews.
• Maintain a library of reusable program structures, slide assets, and case study inserts; flag gaps in the existing content library proactively.
4. Research & Market Intelligence
• Track trends across the AI / GenAI / LLM ecosystem and Data Engineering & Analytics — translate findings into usable inputs for outreach, pitching, and offering design.
• Identify new solution opportunities and product ideas based on market signals, customer asks, and competitor moves.
• Benchmark StackRoute's offerings against competitors; surface gaps and differentiation angles for Senior SMEs and Practice Leads to act on.
5. Internal Collaboration
• Work fluidly with Delivery, Sales, and external SMEs to ensure solutions designed on paper actually work in delivery — surface feasibility risks early, not late.
• Coordinate inputs across Practice teams during pursuit cycles; hand off to delivery with documentation that captures customer commitments and success metrics.
Must Have Technical & Functional Skills
• Good understanding of terminologies in Data Engineering (ETL, pipelines, data lakes), Data Analytics & BI concepts, and Machine Learning fundamentals, AI tools ( not technical expertise but L1-L2 knowledge should be present from application standpoint).
• Awareness of GenAI / LLM vocabulary — prompt engineering, RAG, APIs — with enough depth to hold a credible first conversation with a technical stakeholder.
• Strong PowerPoint skills (client-ready decks), Excel for effort estimation and costing basics, and structured documentation — proposals, SoWs, one-pagers.
• Strong problem-solving and structured thinking — breaks complex requirements into clear, communicable solutions.
• Comfortable communicating with both technical and non-technical stakeholders; good storytelling and presentation instincts; understanding of L&D context is a plus.
Qualifications & Experience
Required:
• 5-15 years in the education products, or in solutioning, pre-sales, or consulting roles with exposure of 3-5 years in Data/AI/Analytics.
• Bachelor's or Master's in Computer Science, Data Science, Engineering, or a related discipline.
Nice to Have competences:
• Prior pre-sales, proposal writing, or design development experience.
• Certifications in cloud, data, or AI platforms (AWS, Azure, GCP, or model-provider certifications).
Core Competencies
· Structured Thinking: Organises ambiguous client and technical inputs into logical, buyer-relevant narratives. Builds proposals that flow from problem to solution.
· Solution Articulation: Translates Data & AI capabilities into crisp, persona-specific stories. Adapts the pitch for a CTO, L&D Head, or BU Head without losing substance.
· Research & Synthesis: Gathers and distils large volumes of information into sharp, usable outputs. Knows what to include and what to leave out.
· Written Communication: Writes a tight brief, a clean slide, and a clear email. Adapts register from internal working notes to buyer-facing collateral.
· Curiosity & Learning Agility: Picks up new tools, concepts, and sectors quickly. Tracks AI / GenAI shifts proactively rather than waiting to be told what to read.
· Bias for Action: Ships a useful 10-slide deck on time rather than a polished 20-slide deck that's late. Comfortable with iteration over perfection.

About NIIT
About
Similar jobs (10)
Designation: AI Adoption specialist/AI Consultant
Location: Ahmedabad
Work Timings: Primarily Normal Shift (Flexible to support US clients)
Role Overview:
We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.
Key Responsibilities:
Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.
Assess client requirements and prepare solution strategies using AI tools and methodologies.
Work with internal teams to design, propose, and help execute AI-powered solutions.
Provide AI-based recommendations that align with the client’s business objectives.
Communicate technical possibilities in a business-friendly manner to decision-makers.
Take ownership of the client journey from discovery to implementation and support.
Stay updated with AI trends, tools, and real-world use cases that can benefit clients.
Required Skills & Qualifications: Minimum 2+ Years of hands on experience into Custom AI Development. Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency. Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologis). Some hands-on experience in AI projects – either through execution, coordination, or implementation. Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders. Strong problem-solving mind set with the ability to translate business needs into AI opportunities. Flexible to work with international clients, especially in the US time zone as needed.
Role overview
Antier Solutions is hiring a Business & Solutions Consultant to lead discovery, solution design and delivery alignment for a large enterprise client.
The role is domain agnostic: we want a structured problem-solver who can step into any industry, learn it fast and turn business goals into technology solutions our engineering teams can build.
Item Detail
- Position Business & Solutions Consultant
- Engagement Enterprise client account (client-facing)
- Reports to Delivery Head / Practice Lead
- Experience 6–12 years in consulting or digital transformation
- Preferred background Big 4 or equivalent top-tier consulting firm
- Location Mohali / Chandigarh (hybrid; client travel as needed)
Key responsibilities
Client engagement and discovery
• Act as the trusted advisor to client senior stakeholders (CXO, VP, Director level).
• Run discovery workshops, stakeholder interviews and process walkthroughs to capture business goals, pain points and constraints.
• Quickly build working knowledge of the client's industry, operating model, regulations and competitors.
Business analysis and solution design
• Convert business needs into business requirement documents, functional specifications, user stories and acceptance criteria.
• Map as-is and to-be processes, run gap and fit-gap analysis, and define the target operating model where needed.
• Work with architects and engineering leads to shape technically feasible solutions across web, mobile, cloud, data and AI platforms.
• Build business cases, ROI and cost-benefit models, and solution roadmaps with clear phasing.
Delivery and governance
• Own scope, requirements traceability and change control; keep business and technology teams aligned through the delivery cycle.
• Support sprint planning, backlog prioritisation, UAT and go-live readiness.
• Track risks, dependencies and assumptions; escalate early with a recommended mitigation.
• Prepare steering committee decks, status reports and executive summaries.
Pre-sales and growth
• Support proposals, RFP/RFI responses, solution presentations and estimates with the Business Development team.
• Identify upsell and expansion opportunities within the client account.
• Join client and prospect meetings with the sales team as the business and solution expert, and lead technical-business discovery calls to qualify opportunities.
• Translate client needs into compelling solution narratives, demos, proof-of-concept scopes and value propositions that differentiate Antier.
• Prepare effort estimates, commercial models, pricing inputs and delivery plans with delivery and finance teams.
• Co-own large proposals and enterprise deal pursuits: win themes, executive presentations and defense of the solution during client negotiations.
• Build reusable sales assets such as case studies, capability decks, solution accelerators and industry point-of-view papers.
• Use consulting networks and industry knowledge to open doors, support lead generation and strengthen relationships with enterprise decision makers.
• Provide market and competitor insights to the leadership team to sharpen go-to-market strategy and positioning.
• Support a smooth handover from sale to delivery so that commitments made in pre-sales are executed.
Required qualifications and experience
• Bachelor's degree in engineering, business or a related field; MBA or equivalent postgraduate degree from a reputed institute preferred.
• 6–12 years of experience in management or technology consulting, with at least 3 years at a Big 4 firm (Deloitte, EY, KPMG, PwC) or a comparable firm such as Accenture, McKinsey, BCG or Bain.
• Proven record on client-facing engagements for large enterprises across more than one industry or domain.
• Hands-on experience in requirements gathering, process mapping and solution definition for technology or digital transformation programs.
• Experience working with engineering teams on delivery, in Agile or hybrid models.
• Prior exposure to enterprise platforms, data and analytics, cloud, AI or blockchain programs is a strong plus.
• Demonstrated experience supporting pre-sales or business development: proposals, RFP responses, solution pitches and client presentations that contributed to deal wins.
Skills and competencies
Area What we look for
Structured problem solving Hypothesis-driven thinking, issue trees, MECE analysis, root-cause analysis
Domain agility Learns a new industry within weeks and speaks credibly with business owners
Communication Crisp writing, executive presentations, workshop facilitation, active listening
Stakeholder management Handles senior and conflicting stakeholders; builds trust and drives decisions
Technical fluency Understands architecture, APIs, integrations, data flows and cloud basics well enough to challenge and translate
Analytical tools Advanced Excel and PowerPoint; Jira, Confluence, Visio or Lucidchart; working knowledge of Power BI or Tableau
Delivery discipline Agile and Scrum, backlog management, risk and change management
Ownership Works independently on ambiguous problems and takes accountability for outcomes
Good to have, and what we offer
Good to have
• Certifications such as CBAP, PMP, PMI-PBA, CSPO or TOGAF.
• Experience with global clients across the US, UK, Middle East or APAC.
• Exposure to RFP and proposal writing for technology services.
What we offer
• Direct exposure to a large enterprise client and senior decision makers.
• Close collaboration with Antier's architects and engineering teams on AI, blockchain, fintech and enterprise platforms.
• A defined growth path into Principal Consultant or Client Partner roles.
• Competitive compensation aligned to Big 4 experience, with performance-linked rewards.
The role
A working product and a working deployment are two different things. You are the person who closes that gap.
You sit inside the client's head office. You get the deployment live, you get their teams using the dashboards, and you own whether the AI is returning something worth acting on. Every client is different: different languages on the floor, different store noise, different vocabulary for the same product, different CRM, different idea of what a good conversation looks like. The core platform does not change for each of them. You are the layer that makes it fit, and you are the one the client meets.
You are encouraged to spend time in stores. The engineers who do the best work here are the ones who have stood on a shop floor and watched where the pitch and the pipeline actually break. Nobody will make you go. You will also spend real time in the codebase, because you fix what you find rather than filing it.
What you build has a commercial edge to it. A pilot converts when the client sees the result they were promised, and an account grows when a second team inside it sees what is already sitting in their data. Both of those outcomes are yours to deliver, not somebody else's to chase.
How you will work
You design the deployment, you build it, and you own whether it holds up on a Saturday evening in a crowded store. Nobody hands you the plan, and nobody hands you the spec. You write both.
The decisions are yours. Which integration is worth the week, which vertical taxonomy needs building, what ships in the pilot and what waits, and when to tell a client that the thing they are asking for is the wrong thing to build. You go and find out what a client needs before anyone writes a line of code.
You will not be doing it alone. There are founders, AI engineers and product people around you, and they will build alongside you. What nobody will do is tell you what the client needs. That call is yours.
The work compounds if you do it well. What you learn on one deployment becomes a specification, then code, then a pattern the next one starts from. A year in, the deployments you designed should be running without you, and a new client should take a fraction of the time the first one did.
What you will do
Own the deployment end to end. Device provisioning, store connectivity, data flowing, first insight in front of the client. Get from kickoff to something real inside
the pilot window, and know by the halfway mark whether it is in trouble.
Get their HQ using it. A dashboard nobody opens is a failed deployment. Sit with the sales, marketing and L&D teams, show them what is in their own data, and
make sure the people who asked for this are actually looking at it every week.
Make the AI work on their floor. Their languages, their store noise, their product vocabulary. Benchmark transcription and speaker separation on their actual
audio, and fix what fails instead of explaining it away.
Build the vertical. Intent taxonomies, objection maps and prompt libraries for the category you are deployed into. A jewellery floor and an electronics floor do not
share a conversation model.
Wire it into their systems. CRM and POS integrations, so conversation data connects to what actually got sold and the insight can be checked against reality.
Build what the client asks for. Custom reports, dashboards and agents. Ground everything in source conversations and verify it before it ships, because a confident
wrong number costs an account.
Close the pilot. A pilot converts on results, not on effort. Know what the client agreed to judge this on, work backwards from it, and make sure the output in front of
their leadership at the end is the thing they asked for.
Grow the account. The same intelligence is worth something to marketing, L&D and category teams inside the same client. Spot which of them would benefit, show them what is already in their data, and hand a real opening to the account team.
Push it back into the product. Turn one-off client work into something the platform does by default, so the next deployment starts further ahead than this one did.
What we are looking for
Must have
- 0 to 5 years of experience. A consulting internship or an analyst role is the closest match to what this job actually asks for, but we care more about what you can do than where you did it
- Coding ability, ideally Python. Degree, internship, first job or your own projects. What we want to see is something you built that other people actually used
- Excel or Sheets at a real working level. A lot of the first conversation with a client happens in a spreadsheet before it ever happens in a dashboard
- The ability to explain a complicated idea simply. You will be taking AI output to people who do not think about models, and the explanation matters as much as the result
- Comfort at the boundaries. APIs, data pipelines, some frontend, some hardware when a device misbehaves
- An eye for where a deployment turns into more business, and the willingness to raise it yourself
- Heavy hands-on LLM usage. Prompts, evaluations, retrieval, and a clear view on where these tools break
- Fluent English and Hindi. A third Indian language counts for a lot, since the useful conversations happen on store floors and not only in HQ meeting rooms
- The instinct to go and find out what a client needs rather than waiting to be told
Good to have
Speech or audio work. Transcription, diarization, voice activity detection, or
anything that survives noisy real-world recording
Embedded or IoT experience, on ESP32 or similar
SQL and experience building things customers actually look at
Side projects, hackathons or internships where you shipped without a spec
and it worked
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.
🚀 We’re Hiring | Data Scientist 🧠📊
Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!
🔹 Experience: 8+ Years
🔹 Must-Have Skills:
🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization
📍 Location: Pune
💼 Work Mode: Work from Office
If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!
📩 Interested? Kindly text
#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow
Role Overview
As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact.
Key Responsibilities
Data Science & Machine Learning
- Analyze structured and unstructured data to identify patterns, trends, and business opportunities.
- Perform exploratory data analysis (EDA), feature engineering, and data preparation.
- Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.
- Apply statistical techniques to solve business problems and validate model performance.
- Design and execute experiments to improve model accuracy and business outcomes.
AI Solution Development
- Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.
- Translate business requirements into scalable data science approaches.
- Contribute to Generative AI and advanced analytics initiatives where applicable.
- Document methodologies, model performance, and key findings.
Required Technical Skills
- Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.
- Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.
- Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.
- Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.
- Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.
- Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.
- Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.
- Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.
- Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 2–4 years of experience developing machine learning or data science solutions.
- Experience working on end-to-end data science projects in a business environment.
Nice to Have
- Exposure to Generative AI, LLMs, RAG, or Agentic AI.
- Experience with Computer Vision or Natural Language Processing (NLP).
- Familiarity with cloud-based AI platforms.
- Knowledge of construction, engineering, manufacturing, or industrial domains.
- Participation in hackathons, research, Kaggle competitions, or open-source projects.
Soft Skills
Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.
Role Overview
The Business Analyst for the CCX Customer Success AI Acceleration workstream partners closely with Engineering, Product Management, and Program teams to translate customer success strategy and AIdriven use cases into clear, actionable requirements that enable scalable delivery. This role sits on the engineering side of the house, acting as a connective layer between business intent, technical execution, and AIenabled platform outcomes.
The Business Analyst ensures that AI acceleration initiatives across the Customer Success Platform are well‑defined, appropriately prioritized, and traceable from business objectives through system design and delivery. This includes refining problem statements, documenting requirements, supporting backlog readiness, and helping teams move quickly without losing alignment or clarity.
Requirements
• Proven experience as a Business Analyst supporting engineering teams, preferably in enterprise, platform, or SaaS environments.
• Strong ability to translate business needs, customer success objectives, and AI use cases into clear functional and non‑functional requirements.
• Experience working on AI‑enabled or data‑driven products, including concepts such as automation, recommendations, agentic workflows, or insights powered by analytics.
• Ability to partner effectively with Engineers, Product Managers, Technical Program Managers, and UX to support backlog refinement and delivery planning.
• Experience creating and maintaining artifacts such as user stories, acceptance criteria, process flows, data mappings, and dependency documentation.
• Comfort operating in fast‑paced, iterative delivery environments, supporting AI acceleration efforts where requirements evolve quickly.
• Strong analytical skills with the ability to identify gaps, risks, dependencies, and edge cases early in the development lifecycle.
• Clear written and verbal communication skills, with the ability to align technical and non‑technical stakeholders.
• Familiarity with ServiceNow‑style enterprise platforms, customer success workflows, or complex system integrations is a strong plus.
• Bachelor’s degree in Business, Information Systems, Engineering, or a related field—or equivalent professional experience.

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered,
Hiring: 10 openings for Associate Data Forward Deployed Engineer (0–2 yrs) for a fast-growing AI platforms & services company, Hyderabad (confidential client) via Ziro.digital.
Location: Hyderabad (onsite, full-time). Open to candidates from anywhere in India willing to relocate. Experience: 0–2 years. 2024/2025/2026 graduates welcome (B.Tech/B.E/MCA/M.Sc CS/IT or related).
What you'll do: build data pipelines end to end (ingest, transform, model, deliver), work with clients on their data, and use AI for query generation, data quality and debugging.
Must have: strong SQL (write, read, tune); Python for data; SQL Server and/or Postgres; at least one end-to-end data pipeline; data-analysis fundamentals; a GitHub with data projects.
Good to have: S3/Azure Blob, Airflow/mage.ai, DBT/Fabric, Snowflake/Databricks/BigQuery, GitLab CI/CD, Grafana, LLM/RAG awareness.
Compensation & terms: 6-month paid internship at ₹20,000/month, then ₹7 LPA CTC on conversion. Relocation to Hyderabad required.
Selection: Ziro assessment (Communication, Technical, AI interview, Coding), then the company's rounds (aptitude, AI screening, project build, in-office hackathon, technical panel, leadership).
Apply by Wed 21 Oct 2026.
Screening questions (please answer in your application):
1) Willing to relocate to Hyderabad and work onsite?
2) Do you accept a 6-month internship at ₹20k/month, then ₹7 LPA?
3) GitHub link + one project you built.
4) Graduation year, current city, notice period.
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.










