Live opening · Posted 14 days ago

Principal solution architect

ShellKode · Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 14 days ago
CompanyShellKode
LocationKarnataka, India (On-site)
Work modeNo
SourceLinkedin
Listed14 days ago

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About the role

Description supplied by the original job listing.

JOB DESCRIPTION
Solutions Architect
About ShellKode
ShellKode is a born-in-the-cloud company that specializes in Modernization, Security, Data, Generative AI, and AI/ML. Our industry specialized solutions and services help organizations realize tangible business value and drive transformative growth. Our offerings span Financial Services, Retail, Logistics, and Healthcare with over 80 specialized industry solutions across data and GenAI.
Role Overview
Role Title
Solutions Architect (AWS & Agentic AI)
Business Unit
Cloud | Data | AI / GenAI / ML
Reports To
Principal Solutions Architect
Matrixed Reporting To
Pre-Sales & Solutioning Lead
Scope
Solution architecture across multiple client engagements and pursuits
Location
Mumbai / Bangalore / Chennai - India
What is the role about?
The Solutions Architect is a hands-on, customer-facing technical leadership role that designs and drives end-to-end solutions across ShellKode's Cloud, Data, and AI/GenAI portfolio. The Solutions Architect partners closely with Pre-Sales, Delivery, and client stakeholders to translate business problems into robust, scalable, and cost-optimized architectures predominantly on AWS with deep specialization in Agentic AI, Generative AI, and modern data platforms. Beyond design, the role is a trusted advisor to customers: running discovery and design workshops, leading enablement sessions, and acting as a thought leader who represents ShellKode's point of view in the market. The role blends architecture depth, applied AI expertise (including Anthropic and OpenAI model ecosystems), and outstanding communication and facilitation skills. The Solutions Architect owns solution quality from opportunity through to delivery hand-off, championing reusable accelerators and reference architectures that strengthen ShellKode's competitive edge.
What you will do
As a Solutions Architect, you will be responsible for the following:
Solution Architecture & Design
Own end-to-end solution architecture for client engagements across Cloud, Data, and AI/GenAI domains, ensuring designs are scalable, secure, resilient, and cost-optimized.
Architect cloud-native solutions predominantly on AWS compute, storage, networking, serverless, containers, and managed data/AI services.
Design Agentic AI and Generative AI solutions including multi-agent orchestration, tool/function calling, RAG pipelines, prompt and context engineering, and evaluation/guardrail frameworks.
Produce solution architecture documents, high- and low-level designs, architecture diagrams, and reference architectures that guide delivery teams.
Define non-functional requirements performance, scalability, security, observability, and FinOps and embed them into every design.
Customer Engagement & Workshops
Act as a trusted technical advisor and primary customer-facing architect throughout the engagement lifecycle, building strong relationships with client stakeholders from engineers to executives.
Plan and facilitate customer-facing workshops discovery, design, Well-Architected reviews, GenAI/AI ideation, and Immersion Day–style sessions that align technical solutions to business outcomes.
Lead whiteboarding sessions and translate complex architecture and AI concepts into clear, business-relevant narratives for both technical and non-technical audiences.
Run proof-of-concept and prototype sessions with customers to de-risk decisions and accelerate buy-in.
Gather and synthesize customer requirements, constraints, and success criteria into actionable solution direction.
Enablement & Thought Leadership
Design and deliver internal enablement brown-bags, bootcamps, and certification-prep sessions to grow AWS, GenAI, and Agentic AI capability across ShellKode teams.
Create reusable enablement assets: reference architectures, playbooks, demos, and hands-on labs.
Act as a thought leader for ShellKode authoring blogs, whitepapers, and solution briefs, and speaking at webinars, meetups, and industry events.
Represent ShellKode's point of view on AWS, Agentic AI, GenAI, and data trends with customers, partners, and the broader community.
Mentor engineers and aspiring architects, sharing knowledge and raising the technical bar across the practice.
Applied AI & GenAI Engineering
Select and integrate foundation models across providers Amazon Bedrock, Anthropic (Claude), and OpenAI (GPT) matching model capabilities to use-case, latency, and cost constraints.
Design and prototype Agentic AI systems using frameworks such as Bedrock Agents, LangGraph, LangChain, MCP, and custom orchestration patterns.
Architect RAG and knowledge-grounding pipelines embeddings, vector stores, chunking strategies, retrieval quality, and hallucination mitigation.
Establish evaluation, observability, and responsible-AI guardrails for GenAI solutions, including model evaluation, red-teaming, and cost/token governance.
Stay current with the rapidly evolving model landscape and advise on adoption of new capabilities from AWS, Anthropic, and OpenAI.
Data Architecture
Design modern data platforms lakehouses, pipelines, streaming architectures, and governed data products that power analytics and AI workloads.
Architect data ingestion, transformation, and serving layers on AWS (e.g., S3, Glue, Redshift, Athena, EMR, Kinesis, Lake Formation) and complementary tooling such as dbt.
Ensure data quality, lineage, security, and privacy are engineered into solutions from the ground up.
Pre-Sales & Solution Engineering
Partner with Pre-Sales to drive technical solutioning for new opportunities across the BU's domains.
Lead the creation of technical proposals, solution architecture documents, effort estimates, and BOM/BOQ for RFPs and RFIs.
Present and defend technical solutions in client discussions and solution reviews, articulating architecture approach, trade-offs, and delivery methodology.
Build reusable solution accelerators, reference architectures, and demos that shorten sales cycles and strengthen ShellKode's pre-sales assets.
Provide inputs to BU leadership on capability gaps versus pipeline demand and emerging technology trends.
Technical Leadership & Delivery Enablement
Provide hands-on guidance on architecture, engineering decisions, and problem resolution during delivery.
Drive design and code reviews, proof-of-concept initiatives, and technical spike evaluations.
Champion engineering excellence CI/CD, automated testing, DevSecOps, containerization, and platform reliability.
Serve as an escalation point for complex technical and architectural challenges across engagements.
Governance & Stakeholder Management
Ensure solutions adhere to architectural guidelines, security standards, and the AWS Well-Architected Framework.
Communicate architecture decisions and trade-offs clearly to both technical teams and business stakeholders.
Coordinate with Delivery, Pre-Sales, and Sales teams on cross-functional solution deliverables.
What will you need to have?
Experience
Minimum 10 years of experience in the software/technology services industry.
Minimum 3 years in a hands-on solution architecture role within Cloud, Data, or AI/GenAI/ML domains.
Proven track record of architecting and delivering complex, production-grade solutions on AWS.
Demonstrated experience designing and shipping Generative AI and/or Agentic AI solutions.
Demonstrated experience in customer-facing roles running workshops and advising client stakeholders up to executive level.
Technical Depth
AWS: Strong hands-on architecture experience across compute, serverless (Lambda), containers (ECS/EKS), storage, networking, IAM/security, and cloud-native development; familiarity with the Well-Architected Framework and FinOps.
Agentic AI & GenAI: Practical experience with LLMs, agent orchestration, tool/function calling, RAG, prompt/context engineering, model evaluation, and guardrails.
Model Ecosystems: Hands-on experience with Amazon Bedrock and with Anthropic (Claude) and OpenAI (GPT) APIs and their respective strengths, limits, and cost profiles.
Data: Experience with data platforms, lakehouses, pipelines, streaming architectures, and tools such as Glue, Redshift, Athena, EMR, Kinesis, and dbt.
Sound unde

Work arrangement
No

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