About TresVista & Descrial

TresVista is a global platform providing sophisticated solutions to clients combining domain expertise, technology, and human capital. Our unique model allows clients to achieve excellence through embracing best in class AI and human capital with an offshore resource model.

Descrial, the dedicated technology product unit, is at the forefront of innovation leveraging AI and intelligent automation to build workflow-native solutions. Our approach goes beyond traditional product development, integrating design research, data engineering, and applied AI to build solutions that are scalable, evidence-based, and user-centric. For experienced product leaders and technologists- Descrial offers the prospect to define next-generation tools that transform how investment professionals interact with data and make decisions.

Descrial is focused on building solutions delivering smarter and faster ways to conduct diligence, analysis, and make investment decisions.

Role Overview

As Senior Solution Architect, you will hold the most senior architecture role in the company and own the end-to-end technical vision. You will set the architecture for our three product pillars -- document intelligence, AI orchestration, and context building -- and ensure they come together as one coherent, secure, and scalable platform. This is a hands-on leadership role for an architect who moves fluidly between deep systems design and AI system design, who can translate the realities of alternative investing into product architecture, and who raises the technical bar for the entire engineering organization.

You will partner closely with founders, product, and engineering leadership to turn an ambitious product vision into architecture that scales -- balancing speed of delivery with the confidentiality, auditability, and reliability that institutional investors demand.

Roles and Responsibilities

Architecture leadership

Own the overall technical architecture and a multi-year architecture roadmap spanning the Java Operating System and the Python AI layer.

Act as the senior-most technical authority: set standards,



make and document key design and build-vs-buy decisions, and resolve cross-cutting architectural trade-offs.

Establish architecture governance -- reference designs, patterns, and review practices -- that the engineering team can consistently build against.

Document intelligence

Architect the data room and document pipeline: ingestion, classification, extraction, and structuring of deal diligence documents and other unstructured materials.

Design how documents are indexed and made available for query and decisioning, so investment teams can reliably ask questions of their deal data and act on the answers.

Ensure document handling meets the confidentiality, access-control, and auditability expectations of the alternative investment industry.

AI orchestration

Design the orchestration architecture within AI Assist that runs research, diligence, and other multi-step workflows across the deal lifecycle.

Build scalability in the orchestration layer for multi tenancy, human in the loop and diverse work flow execution needs.

Decide architecture - using third party systems like temporal or building a grounds up approach

Build for traceability and evaluation, so AI-driven outputs used in diligence and decisioning can be traced from input to output and continuously assessed.

Context building

Architect the context-building layer that assembles the right information -- from the data room and other sources -- to ground AI reasoning for each task.

Decide architecture - using third party systems like MemO or building a grounds up approach

Balance context richness against performance, cost, and data-boundary constraints.

Platform, security, and scale

Ensure the Java and Python components integrate cleanly into one platform,



with well-defined interfaces, data flows, and boundaries.

Architect for scale, resilience, and performance as data volumes and workflow complexity grow.

Embed security, privacy, and compliance-by-design, given the sensitive and high-value nature of alternative investment data.

Prerequisites

Experience

Extensive experience (typically 15+ years) designing and building complex, production-grade software systems, including several years in a principal, staff, or architect-level capacity.

Proven track record owning end-to-end architecture for a platform or product at scale -- ideally in a high-growth environment where you remained hands-on.

Core engineering

Deep expertise in Java for building robust, high-performance backend systems and services (our Operating System is Java-based).

Strong proficiency in Python, particularly for AI and data workloads (our AI Assist layer is Python-based).

Strong foundation in distributed systems, API and service design, data modeling, and system integration.

Experience architecting for scale, resilience, performance, and observability.

AI and data

Hands-on experience architecting AI/LLM-powered systems -- orchestrating models, tools, and agents into reliable, observable workflows.

Experience with document intelligence and unstructured data: ingestion, extraction, classification, indexing, and search over large document sets.

Familiarity with evaluation and traceability for AI systems -- measuring output quality and tracing results from input to output.

Security and data handling

Strong grounding in security, privacy, access control, and auditability, with comfort designing for highly sensitive and confidential data.

Education

Engineering or Management degree from a premier Institute (IIT or other Grade A institutes)

Compensation

Our compensation approach is built to attract best in class professionals.

Required Skills

Solution Architecture, Distribution system, API Design, Workflow Orchestration, Java, Python, AI, LLM, AI Orchestration, RAG, Vector, Cloud Architecture, Security Access

📌 Senior Vice President (Bengaluru)
🏢 TresVista Financial Services
📍 Bengaluru