Software Engineering / Technology

Client is seeking a hands-on, forward-thinking Specialty Software Engineer to help build and scale a high-impact Research & Innovation Engineering practice focused on identifying, evaluating, and recommending emerging technologies-turning opportunities into measurable enterprise value. This is a unique opportunity to shape the technical foundation of an innovation pipeline that accelerates enterprise transformation through evidence-based adoption and investment decisions.
In this role, you will drive structured, secure, and automated technology evaluations by leveraging an existing PoC Lab platform to enable rapid, parallel, and isolated testing of emerging solutions. You will partner with vendors and platform teams to provision and tailor use-case-specific environments, maximizing reuse while minimizing friction.
You will define and operationalize standardized evaluation frameworks-including test patterns, success criteria, artifact models, scoring rubrics, and reporting structures-and build automated assessment pipelines that deliver consistent, objective, and decision-grade outcomes. Leveraging modern AI/agent-based approaches, you will accelerate testing, scoring, and insight generation, bringing speed, rigor, and repeatability to every evaluation.
You will play a pivotal role in advancing Client's technology capabilities by rigorously validating vendor solutions and translating results into defensible, data-driven insights that shape high-impact adoption and investment decisions-unlocking commercial value through improved efficiency, reduced costs, and faster time-to-value.
Given the increasing shift toward AI-enabled technologies, this role is ideal for an engineer who thrives in fast-paced, ambiguous environments and brings deep expertise in AI, cloud-native engineering, and automation.

Lead end-to-end PoC execution by leveraging the existing PoC Lab platforms, partnering with vendors and lab teams to rapidly provision and tailor use-case-specific environments with minimal friction and maximum reuse.
Build and apply AI-enabled automated assessment pipelines (test orchestration, data collection, validation, scoring, and results synthesis) to drive speed, accuracy, objectivity, and scalability of evaluations.
Leverage AI/ML and agent-based approaches to streamline the full evaluation lifecycle-including intake, product scouting, market analysis, test execution, intelligent scoring, anomaly detection, and insight generation.
Ensure all evaluations adhere to enterprise security, compliance, and auditability standards, aligned with Architecture, InfoSec, and Risk requirements.
Develop structured, evidence-based PoV outputs and executive-ready recommendations grounded in comparative scoring and measurable outcomes.
Maintain a centralized, reusable repository of evaluation patterns, artifacts, configurations, and outcomes to enable benchmarking, knowledge reuse, and continuous improvement.
Provide technical leadership in vendor assessments and executive reviews, ensuring transparency, rigor, and alignment to strategic and commercial objectives.
Lead and mentor engineers, reinforcing a culture of standardization, automation, and measurable impact.
5+ years of software/platform engineering experience, including hands-on delivery of at least one production-grade Agentic AI solution (preferred).
4+ years of experience leading end-to-end PoC evaluations in collaboration with third-party lab/platform teams and vendors, including defining scope, success criteria, standardized test patterns, execution plans, and scoring frameworks, while coordinating environment readiness, connectivity, access, and execution workflows across diverse technologies.
3+ years of experience in cloud-native, containerized environments (public/private cloud), with the ability to assess integration, operability, scalability, and risk of vendor solutions.
3+ years of experience enabling repeatable environment configuration and building or supporting automated evaluation frameworks, including test orchestration,
validation, and scoring, to standardize, scale, and accelerate PoC assessments while validating vendor deployment patterns.
3+ years of strong Agile execution skills in a fast-moving, cross-functional environment.
3+ years of excellent technical writing and stakeholder communication skills to produce decision-ready artifacts (PoV, findings summaries, scoring inputs, recommendations).

Advanced application of AI/ML and agentic systems to transform scouting, assessment, and evaluation lifecycles-enabling intelligent orchestration, automated competitive analysis, adaptive test generation, and production of investment-grade insights (e.g., structured memos, comparative scoring, and executive-ready synthesis)
Advanced Infrastructure-as-Code and automation capabilities, including modular architecture, policy-as-code, and CI/CD or GitOps patterns for complex, multi-environment evaluation setups.
Experience embedding automated evaluation ecosystems at scale, including extensible pipelines, reusable test harnesses, and integration with enterprise platforms for continuous evaluation.
Strong experience evaluating SaaS and emerging vendor solutions in regulated enterprise environments, with depth in integration complexity, identity/auth patterns, data flows, operational readiness, and long-term supportability.
Familiarity with enterprise governance and control frameworks, including third-party risk lifecycles, security review processes, and audit-quality evidence expectations in large regulated organizations.
Strong background in platform and infrastructure engineering (e.g. OpenShift, Observability), enabling deep technical judgment and architectural tradeoff analysis during evaluations.
Demonstrated ability to produce executive-level narratives and decision artifacts, including PoVs and "whitepaper-light" analyses that clearly articulate tradeoffs, risks, and recommendation rationale.
Proven experience designing and delivering hackathons at scale, including structuring problem statements, evaluation criteria, judging frameworks, and end-to-end execution.
Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience.
Advanced AI/ML certifications or equivalent applied expertise preferred.

In-office presence: Work from the office in alignment with Client in-office expectations (currently a minimum of 3 days per week) and comply with any future changes to firm RTO guidance or business/function requirements.
Travel : Travel may be required on a limited, business-need basis, subject to approvals and budget guidelines.
Collaborate effectively with engineering, architecture, security/risk, product, business stakeholders, vendors and service providers.
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."