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Presales Engineer – Cloud & AI
Presales Engineer – Cloud & AI

Presales Engineer – Cloud & AI at comprinno · Bengaluru (Bangalore), Pune · 2 - 8 years · ₹15L - ₹22L / yr · Posted 12 Oct 2026

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Presales Engineer – Cloud & AI

Farheen Ansari's profile picture
Posted by Farheen Ansari
2 - 8 yrs
₹15L - ₹22L / yr
Bengaluru (Bangalore), Pune
Skills
AWS Solutions Architect
Presales
skill iconAmazon Web Services (AWS)
Solution Consulting
Cloud Consulting
Technical sales
skill iconKubernetes
security
cloud migration
aws map
Iac
infrastructure as code
Terraform
AWS CloudFormation
Generative AI
Large Language Models (LLM)
Prompt engineering
Agentic AI
Retrieval Augmented Generation (RAG)
AWS Bedrock
Sagemaker
Amazon Q
LangGraph
langchain
CrewAI
Amazon EC2
Amazon VPC
Amazon S3
AWS Lambda
AWS RDS
Amazon RDS
AWS IAM
migration acceleration program
framework
migration evaluator
DevOps
skill iconDocker
CI/CD
cicd
Artificial Intelligence (AI)
SOW
RFI
rfp
architecture diagram
POC
technical proposal
effort estimation
cost optimization
skill iconMachine Learning (ML)

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.
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Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About comprinno

Founded :
2013
Type :
Services
Size :
100-1000
Stage

About

Looking for a cloud consulting company? Comprinno is a trusted cloud managed services provider driving secure cloud transformation. Get started today.
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Support the sales team in explaining technical solutions to prospective clients.

Proposals & Presentations

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Curious about technology and how businesses use it.

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Strong in written and verbal communication.

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Analytical and detail-oriented.

Proactive and willing to take ownership of tasks.

Interested in AI, software, automation, and emerging technologies.

Able to learn quickly in a fast-paced environment.

Qualifications

Bachelor's degree in IT, Computer Science, Business, Engineering, Marketing, or a related field.

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Requirement Gathering

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Solution Research

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Strong Written & Verbal Communication

Analytical & Problem-Solving Skills

Ability to understand AI and software concepts

Technology Exposure


Knowledge or interest in any of the following is an advantage:


Artificial Intelligence & Generative AI

LLMs & AI Applications

AI Automation

Software Development

SaaS Platforms

Web & Mobile Applications

APIs & Integrations

Cloud Technologies

AI Infrastructure

Business Process Automation

Data & Document Intelligence


Deep technical expertise is not mandatory. The ability to understand technology, learn quickly, and communicate its business value is more important.


What We Offer

Competitive salary.

Performance-based growth opportunities.

Direct exposure to founders, clients, and technical teams.

Hands-on experience with AI and software projects.

Opportunity to work across different industries and business problems.

Professional development and career growth.

Fast-paced and collaborative work environment.

Job Details


Job Type: Full-time, Permanent

Work Mode: Work From Office

Location: HSR Layout, Bengaluru

Experience: 1–3 years preferred

Education: Bachelor's degree preferred

Read more
Remote only
4 - 8 yrs
₹10L - ₹30L / yr
Generative AI (GenAI)
Large Language Models (LLM) tuning
Fine-tuning LLMs
Retrieval Augmented Generation (RAG)
skill iconPython
+2 more

Forward-deployed engineers (FDEs) are Mactores' services layer. You embed with the customer's team, own outcomes from discovery through the production cutover, and personally carry the delivery commitment.

The agent platform we deploy absorbs 60–70% of engagement work, discovery, assessment, design, and testing. You absorb the judgment: target architecture, refactoring trade-offs, model selection, cutover strategy, and the decisions an agent platform cannot make. The agent absorbs scale. You absorb judgment. 

This is not a staff-augmentation seat and not an advisory role. You ship.

 

What you will do?

  • Deliver production agentic AI systems and AWS modernization engagements on committed dates across three pillars: Data Platform Modernization, Application & Database Modernization, and AI Agents for Apps.
  • Build and productionize AI agents, orchestration, retrieval pipelines, evaluation harnesses, observability running against real customer data, not demo data.
  • Convert existing products into agents: expose product functionality as callable tools for agent-to-agent composition, or replace form-and-click UX with agent-native, intent-driven interfaces.
  • Convert existing Business processes into agents: expose process functionality as callable tools for agent-to-agent composition, or replace form-and-click UX with agent-native, intent-driven interfaces.
  • Embed directly with customer engineering teams. Run architecture sessions, defend design decisions, and align stakeholders from VP Engineering to CTO.
  • Make agent decisions traceable and defensible, validation runs in parallel with live workloads, and outputs hold up to internal audit and regulators (HIPAA, PCI-DSS, FSI-grade governance where the vertical demands it).
  • Feed field experience back into the platform and practice: your deployment patterns, integration playbooks, and edge cases shape how we deliver.


What are we looking for?

  • Excellent communication skills (English) — verbal and written. Non-negotiable. You will present architecture to customer CTOs, write documents that hold up in audit, and defend judgment calls in the room. If you can build but not explain, this role is not a fit.
  • You have shipped production agentic AI systems on AWS. Not POCs, not notebooks — systems running in production for real users. This is the primary qualification. Be prepared to walk through what you shipped, the decisions you made, and what broke.
  • Deep understanding of agentic architecture — you can design an agent system from first principles and explain why each component exists:
  • Agent design patterns: single-agent vs. multi-agent systems, supervisor/orchestrator patterns, hierarchical agent topologies, planner–executor separation, and when each applies.
  • Orchestration: building and operating orchestrator agents that decompose tasks, route work to specialist agents or tools, and manage state across multi-step workflows (LangGraph, Strands Agents, CrewAI, or equivalent).
  • Memory: short-term/working memory (context management, conversation state) and long-term memory (episodic and semantic stores, vector- and graph-backed retrieval), and the production trade-offs of each.
  • Reflection and self-correction: critique loops, self-evaluation, retry-with-feedback patterns, and evaluation harnesses that catch agent failures before customers do.
  • Tool use and function calling: schema design, tool-selection reliability, error handling, and agent-to-agent composition.
  • RAG and retrieval pipelines: chunking, embedding, hybrid retrieval, reranking, and grounding agent decisions in customer data.
  • Strong AWS production experience: Amazon Bedrock and AWS AI services, plus core platform services (Lambda, API Gateway, DynamoDB, RDS/Aurora, Glue, EMR, Redshift, Kinesis, or similar depending on specialization).
  • Solid software engineering fundamentals Python, TypeScript, CI/CD, infrastructure-as-code, testing-driven development discipline.
  • Experience with data or application modernization (database migration, legacy refactoring, data platform builds) is a strong plus, since agents run against these workloads.
  • Indicative experience: roughly 3–10 years in engineering roles, with agentic AI / GenAI as your current day job. We have demonstrated agent-native expertise over tenure — an engineer with 3–4 years of hands-on agentic AI work typically outperforms a 12-year generalist on this work.


You'll be preferred if you've:

  • US English verbal and written fluency 
  • Delivery experience in one or more of our verticals: Financial Services, Healthcare & Life Sciences, Internet & Software, Manufacturing, or Telco/Media/Entertainment/Gaming/Sports.
  • Model tuning and fine-tuning: systematic prompt engineering and optimization; parameter-efficient fine-tuning (LoRA/QLoRA or similar); instruction tuning; working knowledge of RLHF/DPO; sound judgment on when to fine-tune vs. prompt vs. RAG; and evaluation of tuned models against baselines. Fine-tuning experience on Amazon Bedrock or SageMaker is a plus.
  • Experience with compliance-sensitive AI systems (HIPAA, PCI-DSS, SOC 2, data residency).
  • Knowledge graph, code-analysis (AST), or CDC/streaming experience (Debezium, Kafka/MSK).
  • Solid software engineering fundamentals — Java, C++, Go Lang, .Net, Rust
  • Prior customer-facing consulting or forward-deployed experience.
  • AWS certifications (Solutions Architect Professional, Machine Learning Specialty, or Data Analytics).


Why This Role?

  • You own outcomes, not tickets. FDEs carry the delivery commitment personally — architecture, judgment, and cutover are yours.
  • You work agent-native from day one. Our delivery model would not function without agents. You build with the platform, not around it.
  • You ship. Engagements measured in weeks to production, legacy retired, outcomes named. No archived pilots.
  • You compound. Field delivery informs the Aedeon platform roadmap; the platform's growth expands what you can deliver. Few engineering roles sit in that loop.


Read more
MNC
MNC
Agency job
via VY SYSTEMS PRIVATE LIMITED by aafia parveen
Bengaluru (Bangalore)
10 - 17 yrs
₹5L - ₹22L / yr
skill iconAmazon Web Services (AWS)
AWS Lambda
AWS RDS

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

  • Review, validate, and optimize existing Terraform code and AWS infrastructure.
  • Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
  • Design, build, and support secure, scalable, and highly available AWS environments.
  • Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
  • Lead infrastructure testing, performance tuning, and production readiness activities.
  • Drive deployment and operationalization of the platform in the Production environment.
  • Implement cloud governance, security, monitoring, and FinOps best practices.
  • Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

  • 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
  • Proven experience designing, deploying, and managing AWS production environments.
  • Strong hands-on experience with Terraform and Infrastructure-as-Code.
  • Experience with CI/CD pipeline automation and DevOps practices.
  • Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
  • Experience in performance optimization, reliability, and cloud cost management (FinOps).
  • Strong scripting and automation skills.
  • Experience integrating enterprise applications through APIs and secure connectivity patterns.


Read more
Wissen Technology
at Wissen Technology
4 recruiters
Shivangi Bhattacharyya
Posted by Shivangi Bhattacharyya
Bengaluru (Bangalore)
5 - 7 yrs
Best in industry
skill icon.NET
skill iconC#
skill iconPython
Large Language Models (LLM)
Agentic AI
+1 more

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.


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