Business Development Manager ( Software )

The Business Development Manager (BDM) is responsible for driving business growth by identifying new opportunities, understanding client needs, and developing software and AI solutions that deliver measurable business value. The role works closely with Sales, Presales, Technical, Engineering, Delivery, and vendor teams to develop winning solutions, support proposals and client presentations, and ensure that proposed solutions are technically feasible, commercially viable, and aligned with customer requirements.

Responsibilities:

Presales & Sales Support

• Partner with account managers and sales engineers to qualify opportunities, understand

customer business drivers, and shape winning software and AI solution strategies.

• Lead technical discovery sessions with customers to translate business requirements into

solution architectures.

• Scope and size software and AI requirements — effort estimation, licensing, infrastructure

sizing, and cost modeling — to support accurate proposals and Bill of Materials (BOM).

• Prepare and deliver compelling technical presentations, demos, and proofs of concept

(PoCs) to prospective and existing clients.

• Respond to RFPs/RFQs and Terms of Reference (ToR) compliance sheets, ensuring

technical accuracy and completeness of proposed solutions.

• Support contract and SOW discussions by clarifying technical scope, assumptions, and

exclusions.

Solution Architecture & Technical Design

• Design end-to-end software solution architectures, including application, integration, data,

and AI/ML components, aligned to customer requirements and industry best practices.

• Apply working knowledge of the Software Development Life Cycle (SDLC) — Agile,

Waterfall, and hybrid methodologies — to plan realistic project timelines and delivery

approaches.

• Design and validate API integrations and MCP (Model Context Protocol) connections

between AI/software platforms and infrastructure systems such as Cisco, Splunk, and

other network, security, and observability platforms.

• Build and demonstrate integration prototypes and automation workflows to validate

solution feasibility before handoff to delivery teams.

• Produce High-Level Design (HLD) documents, architecture diagrams, and technical

documentation to support proposals and project delivery.

• Collaborate with delivery, engineering, and vendor teams to ensure proposed solutions are

implementable and supportable post-sale.

• Provide architectural oversight and governance during implementation to ensure the

delivered solution matches the approved design.

• Serve as the design authority for change requests and scope adjustments after handoff.

• Produce and maintain architecture deliverables (HLD, and where needed LLD inputs) that

comply with UNVRS SDLC phase-gate requirements and traceability standards.

• Contribute reference architectures and reusable design frameworks to UNVRS's internal IP

portfolio, strengthening repeatable, productized capability.

• Help define and maintain solution architecture standards, patterns, and the approved

technology stack for UNVRS engagements.

AI Enablement

• Use AI coding assistants (e.g., Claude Code, OpenAI Codex, or similar tools) to rapidly

prototype integrations, automate repetitive tasks, and accelerate solution design.

• Evaluate and recommend AI tools and platforms that improve the speed and quality of

presales, scoping, and quality assurance work.

• Champion the adoption of AI-assisted workflows within the presales team, including

compliance-sheet response drafting and QA review.

• Perform quality assurance review of proposals, BOMs, and compliance matrices to ensure

technical accuracy, consistency, and alignment with customer requirements before

submission.

• Maintain reusable solution templates, reference architectures, and sizing tools to improve

team efficiency and proposal turnaround time

• Design agentic AI and retrieval-augmented (RAG) solution components including

orchestration, workflow automation, and model integration — into client and internal

solutions.

Business Strategy

• Analyze market trends, competitor offerings, and customer demand.

• Recommend new software solutions, managed services, and AI offerings.

• Develop go-to-market strategies for new software products.

• Identify opportunities for productization and recurring subscription services.

• Collaborate with Marketing on campaigns, webinars, events, and customer enablement

activities.

Core Competencies & Soft Skills

• Consultative selling mindset with strong business acumen and the ability to align

technology recommendations to customer outcomes.

• Strong verbal and written communication skills, able to simplify complex technical

concepts for non-technical stakeholders.

• Confident public speaker comfortable leading executive presentations, workshops, and

technical demonstrations.

• Detail-oriented with strong QA discipline, able to catch inconsistencies in proposals and

compliance documentation.

• Collaborative team player able to work cross-functionally with sales, delivery, and vendor

partners under tight deadlines.

• Self-driven learner who stays current with emerging AI tools, platforms, and integration

patterns.

Tools & Technologies

• Infrastructure/Platforms: Cisco, Splunk, and related network, security, and observability

platforms.

• AI Development Tools: Claude Code, OpenAI Codex, and similar AI coding assistants.

• Integration: REST/SOAP APIs, MCP (Model Context Protocol), webhooks, automation

scripting.

• Presales Deliverables: Bill of Materials (BOM), High-Level Design (HLD) diagrams,

compliance/ToR response sheets, proposals, and SOWs.

Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related

field (or equivalent practical experience).

• 5+ years of experience in a solutions architecture, presales engineering, business

development, or software development role, with direct customer-facing exposure.

• Strong understanding of the SDLC and modern software development practices

(Agile/Scrum, CI/CD, version control).

• Hands-on experience with API design/integration concepts (REST, SOAP, webhooks) and

exposure to MCP (Model Context Protocol) or similar AI-tool integration frameworks.

• Working knowledge of enterprise infrastructure and security platforms such as Cisco

(networking/security) and Splunk (observability/SIEM), or equivalent platforms.

• Practical experience using AI-assisted development tools such as Claude Code, GitHub

Copilot, OpenAI Codex, or similar.

• Demonstrated ability to scope, size, and cost software and AI solutions, and to translate

technical designs into Bills of Materials and proposals.